058: Code Refactoring

23 files changed, 21 insertions, 216 deletions

diff --git a/examples/sentence_level/wmt_2018/common/util/download.py b/examples/sentence_level/wmt_2018/common/util/download.py
deleted file mode 100644
index feacb5a..0000000
--- a/examples/sentence_level/wmt_2018/common/util/download.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from google_drive_downloader import GoogleDriveDownloader as gdd
-
-def download_from_google_drive(file_id, path):
-    gdd.download_file_from_google_drive(file_id=file_id,
-                                        dest_path= path + "/model.zip",
-                                        unzip=True)
\ No newline at end of file
diff --git a/examples/sentence_level/wmt_2018/de_en/monotransquest.py b/examples/sentence_level/wmt_2018/de_en/monotransquest.py
index 8b50388..0dcc5cf 100644
--- a/examples/sentence_level/wmt_2018/de_en/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/de_en/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -21,9 +20,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
-
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/de_en/data/de_en/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/de_en/data/de_en/"
 TEST_FOLDER = "examples/sentence_level/wmt_2018/de_en/data/de_en/"
diff --git a/examples/sentence_level/wmt_2018/de_en/siamesetransquest.py b/examples/sentence_level/wmt_2018/de_en/siamesetransquest.py
index 9137a33..8e5a6ad 100644
--- a/examples/sentence_level/wmt_2018/de_en/siamesetransquest.py
+++ b/examples/sentence_level/wmt_2018/de_en/siamesetransquest.py
@@ -1,25 +1,22 @@
-import csv
 import logging
-import math
 import os
 import shutil
 
 import numpy as np
 from sklearn.model_selection import train_test_split
-from torch.utils.data import DataLoader
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
+
+
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
 from examples.sentence_level.wmt_2018.common.util.reader import read_annotated_file, read_test_file
 from examples.sentence_level.wmt_2018.de_en.siamesetransquest_config import TEMP_DIRECTORY, GOOGLE_DRIVE, DRIVE_FILE_ID, \
     MODEL_NAME, siamesetransquest_config, SEED, RESULT_FILE, SUBMISSION_FILE, RESULT_IMAGE
-from transquest.algo.sentence_level.siamesetransquest import LoggingHandler, SentencesDataset, \
-    SiameseTransQuestModel
-from transquest.algo.sentence_level.siamesetransquest import models, losses
-from transquest.algo.sentence_level.siamesetransquest.evaluation import EmbeddingSimilarityEvaluator
-from transquest.algo.sentence_level.siamesetransquest.readers import QEDataReader
+from transquest.algo.sentence_level.siamesetransquest.logging_handler import LoggingHandler
+from transquest.algo.sentence_level.siamesetransquest.run_model import SiameseTransQuestModel
+
+
 
 logging.basicConfig(format='%(asctime)s - %(message)s',
                     datefmt='%Y-%m-%d %H:%M:%S',
@@ -29,8 +26,6 @@ logging.basicConfig(format='%(asctime)s - %(message)s',
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/de_en/data/de_en/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/de_en/data/de_en/"
@@ -50,10 +45,12 @@ train = train.rename(columns={'original': 'text_a', 'translation': 'text_b', 'ht
 dev = dev.rename(columns={'original': 'text_a', 'translation': 'text_b', 'hter': 'labels'}).dropna()
 test = test.rename(columns={'original': 'text_a', 'translation': 'text_b'}).dropna()
 
+dev_sentence_pairs = list(map(list, zip(dev['text_a'].to_list(), dev['text_b'].to_list())))
+test_sentence_pairs = list(map(list, zip(test['text_a'].to_list(), test['text_b'].to_list())))
+
 train = fit(train, 'labels')
 dev = fit(dev, 'labels')
 
-
 if siamesetransquest_config["evaluate_during_training"]:
     if siamesetransquest_config["n_fold"] > 0:
         dev_preds = np.zeros((len(dev), siamesetransquest_config["n_fold"]))
@@ -68,75 +65,13 @@ if siamesetransquest_config["evaluate_during_training"]:
                     siamesetransquest_config['cache_dir']):
                 shutil.rmtree(siamesetransquest_config['cache_dir'])
 
-            os.makedirs(siamesetransquest_config['cache_dir'])
-
             train_df, eval_df = train_test_split(train, test_size=0.1, random_state=SEED * i)
-            train_df.to_csv(os.path.join(siamesetransquest_config['cache_dir'], "train.tsv"), header=True, sep='\t',
-                            index=False, quoting=csv.QUOTE_NONE)
-            eval_df.to_csv(os.path.join(siamesetransquest_config['cache_dir'], "eval_df.tsv"), header=True, sep='\t',
-                           index=False, quoting=csv.QUOTE_NONE)
-            dev.to_csv(os.path.join(siamesetransquest_config['cache_dir'], "dev.tsv"), header=True, sep='\t',
-                       index=False, quoting=csv.QUOTE_NONE)
-            test.to_csv(os.path.join(siamesetransquest_config['cache_dir'], "test.tsv"), header=True, sep='\t',
-                        index=False, quoting=csv.QUOTE_NONE)
-
-            sts_reader = QEDataReader(siamesetransquest_config['cache_dir'], s1_col_idx=0, s2_col_idx=1,
-                                      score_col_idx=2,
-                                      normalize_scores=False, min_score=0, max_score=1, header=True)
-
-            word_embedding_model = models.Transformer(MODEL_NAME, max_seq_length=siamesetransquest_config[
-                'max_seq_length'])
-
-            pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension(),
-                                           pooling_mode_mean_tokens=True,
-                                           pooling_mode_cls_token=False,
-                                           pooling_mode_max_tokens=False)
-
-            model = SiameseTransQuestModel(modules=[word_embedding_model, pooling_model])
-            train_data = SentencesDataset(sts_reader.get_examples('train.tsv'), model)
-            train_dataloader = DataLoader(train_data, shuffle=True,
-                                          batch_size=siamesetransquest_config['train_batch_size'])
-            train_loss = losses.CosineSimilarityLoss(model=model)
-
-            eval_data = SentencesDataset(examples=sts_reader.get_examples('eval_df.tsv'), model=model)
-            eval_dataloader = DataLoader(eval_data, shuffle=False,
-                                         batch_size=siamesetransquest_config['train_batch_size'])
-            evaluator = EmbeddingSimilarityEvaluator(eval_dataloader)
-
-            warmup_steps = math.ceil(
-                len(train_data) * siamesetransquest_config["num_train_epochs"] / siamesetransquest_config[
-                    'train_batch_size'] * 0.1)
-
-            model.fit(train_objectives=[(train_dataloader, train_loss)],
-                      evaluator=evaluator,
-                      epochs=siamesetransquest_config['num_train_epochs'],
-                      evaluation_steps=100,
-                      optimizer_params={'lr': siamesetransquest_config["learning_rate"],
-                                        'eps': siamesetransquest_config["adam_epsilon"],
-                                        'correct_bias': False},
-                      warmup_steps=warmup_steps,
-                      output_path=siamesetransquest_config['best_model_dir'])
+            model = SiameseTransQuestModel(MODEL_NAME)
+            model.train_model(train_df, eval_df)
 
             model = SiameseTransQuestModel(siamesetransquest_config['best_model_dir'])
-
-            dev_data = SentencesDataset(examples=sts_reader.get_examples("dev.tsv"), model=model)
-            dev_dataloader = DataLoader(dev_data, shuffle=False, batch_size=8)
-            evaluator = EmbeddingSimilarityEvaluator(dev_dataloader)
-            model.evaluate(evaluator,
-                           result_path=os.path.join(siamesetransquest_config['cache_dir'], "dev_result.txt"))
-
-            test_data = SentencesDataset(examples=sts_reader.get_examples("test.tsv", test_file=True), model=model)
-            test_dataloader = DataLoader(test_data, shuffle=False, batch_size=8)
-            evaluator = EmbeddingSimilarityEvaluator(test_dataloader)
-            model.evaluate(evaluator,
-                           result_path=os.path.join(siamesetransquest_config['cache_dir'], "test_result.txt"),
-                           verbose=False)
-
-            with open(os.path.join(siamesetransquest_config['cache_dir'], "dev_result.txt")) as f:
-                dev_preds[:, i] = list(map(float, f.read().splitlines()))
-
-            with open(os.path.join(siamesetransquest_config['cache_dir'], "test_result.txt")) as f:
-                test_preds[:, i] = list(map(float, f.read().splitlines()))
+            dev_preds[:, i] = model.predict(dev_sentence_pairs)
+            test_preds[:, i] = model.predict(test_sentence_pairs)
 
         dev['predictions'] = dev_preds.mean(axis=1)
         test['predictions'] = test_preds.mean(axis=1)
diff --git a/examples/sentence_level/wmt_2018/en_cs/monotransquest.py b/examples/sentence_level/wmt_2018/en_cs/monotransquest.py
index ea2e7de..4ee9117 100644
--- a/examples/sentence_level/wmt_2018/en_cs/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/en_cs/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -19,8 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/en_cs/data/en_cs/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/en_cs/data/en_cs/"
diff --git a/examples/sentence_level/wmt_2018/en_de/nmt/monotransquest.py b/examples/sentence_level/wmt_2018/en_de/nmt/monotransquest.py
index d2d0369..d626166 100644
--- a/examples/sentence_level/wmt_2018/en_de/nmt/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/en_de/nmt/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -19,8 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/en_de/data/en_de/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/en_de/data/en_de/"
diff --git a/examples/sentence_level/wmt_2018/en_de/smt/monotransquest.py b/examples/sentence_level/wmt_2018/en_de/smt/monotransquest.py
index 86e2b46..37de783 100644
--- a/examples/sentence_level/wmt_2018/en_de/smt/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/en_de/smt/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -19,8 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/en_de/data/en_de/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/en_de/data/en_de/"
diff --git a/examples/sentence_level/wmt_2018/en_lv/nmt/monotransquest.py b/examples/sentence_level/wmt_2018/en_lv/nmt/monotransquest.py
index fc75ca4..948eb30 100644
--- a/examples/sentence_level/wmt_2018/en_lv/nmt/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/en_lv/nmt/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -19,9 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
-
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/en_lv/data/en_lv/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/en_lv/data/en_lv/"
 TEST_FOLDER = "examples/sentence_level/wmt_2018/en_lv/data/en_lv/"
diff --git a/examples/sentence_level/wmt_2018/en_lv/smt/monotransquest.py b/examples/sentence_level/wmt_2018/en_lv/smt/monotransquest.py
index 13a40d5..128a01e 100644
--- a/examples/sentence_level/wmt_2018/en_lv/smt/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/en_lv/smt/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -19,8 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2018/en_lv/data/en_lv/"
 DEV_FOLDER = "examples/sentence_level/wmt_2018/en_lv/data/en_lv/"
diff --git a/examples/sentence_level/wmt_2018/multilingual/monotransquest.py b/examples/sentence_level/wmt_2018/multilingual/monotransquest.py
index c14cded..b29ada7 100644
--- a/examples/sentence_level/wmt_2018/multilingual/monotransquest.py
+++ b/examples/sentence_level/wmt_2018/multilingual/monotransquest.py
@@ -7,7 +7,7 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2018.common.util.download import download_from_google_drive
+
 from examples.sentence_level.wmt_2018.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2018.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2018.common.util.postprocess import format_submission
@@ -20,8 +20,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 languages = {
     # "DE-EN": ["examples/sentence_level/wmt_2018/de_en/data/de_en/",
diff --git a/examples/sentence_level/wmt_2019/common/util/download.py b/examples/sentence_level/wmt_2019/common/util/download.py
deleted file mode 100644
index feacb5a..0000000
--- a/examples/sentence_level/wmt_2019/common/util/download.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from google_drive_downloader import GoogleDriveDownloader as gdd
-
-def download_from_google_drive(file_id, path):
-    gdd.download_file_from_google_drive(file_id=file_id,
-                                        dest_path= path + "/model.zip",
-                                        unzip=True)
\ No newline at end of file
diff --git a/examples/sentence_level/wmt_2019/en_de/monotransquest.py b/examples/sentence_level/wmt_2019/en_de/monotransquest.py
index 1261a42..ccdc5e6 100644
--- a/examples/sentence_level/wmt_2019/en_de/monotransquest.py
+++ b/examples/sentence_level/wmt_2019/en_de/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2019.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2019.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2019.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2019.common.util.reader import read_annotated_file, read_test_file
@@ -18,8 +17,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2019/en_de/data/en-de/train"
 DEV_FOLDER = "examples/sentence_level/wmt_2019/en_de/data/en-de/dev"
diff --git a/examples/sentence_level/wmt_2019/en_ru/monotransquest.py b/examples/sentence_level/wmt_2019/en_ru/monotransquest.py
index e431100..2a1eede 100644
--- a/examples/sentence_level/wmt_2019/en_ru/monotransquest.py
+++ b/examples/sentence_level/wmt_2019/en_ru/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2019.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2019.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2019.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2019.common.util.reader import read_annotated_file, read_test_file
@@ -18,8 +17,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2019/en_ru/data/en-ru/train"
 DEV_FOLDER = "examples/sentence_level/wmt_2019/en_ru/data/en-ru/dev"
diff --git a/examples/sentence_level/wmt_2020/common/util/download.py b/examples/sentence_level/wmt_2020/common/util/download.py
deleted file mode 100644
index 9adc98f..0000000
--- a/examples/sentence_level/wmt_2020/common/util/download.py
+++ /dev/null
@@ -1,7 +0,0 @@
-from google_drive_downloader import GoogleDriveDownloader as gdd
-
-
-def download_from_google_drive(file_id, path):
-    gdd.download_file_from_google_drive(file_id=file_id,
-                                        dest_path=path + "/model.zip",
-                                        unzip=True)
diff --git a/examples/sentence_level/wmt_2020/et_en/monotransquest.py b/examples/sentence_level/wmt_2020/et_en/monotransquest.py
index defe3af..57e23d9 100644
--- a/examples/sentence_level/wmt_2020/et_en/monotransquest.py
+++ b/examples/sentence_level/wmt_2020/et_en/monotransquest.py
@@ -2,26 +2,22 @@ import os
 import shutil
 
 import numpy as np
-import pandas as pd
 import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020.common.util.postprocess import format_submission
 from examples.sentence_level.wmt_2020.common.util.reader import read_annotated_file, read_test_file
 from examples.sentence_level.wmt_2020.et_en.monotransquest_config import TEMP_DIRECTORY, MODEL_TYPE, MODEL_NAME, monotransquest_config, SEED, \
-    RESULT_FILE, RESULT_IMAGE, SUBMISSION_FILE, GOOGLE_DRIVE, DRIVE_FILE_ID
+    RESULT_FILE, RESULT_IMAGE, SUBMISSION_FILE
 from transquest.algo.sentence_level.monotransquest.evaluation import pearson_corr, spearman_corr
 from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQuestModel
 
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FILE = "examples/sentence_level/wmt_2020/et_en/data/et-en/train.eten.df.short.tsv"
 DEV_FILE = "examples/sentence_level/wmt_2020/et_en/data/et-en/dev.eten.df.short.tsv"
diff --git a/examples/sentence_level/wmt_2020/multilingual/monotransquest.py b/examples/sentence_level/wmt_2020/multilingual/monotransquest.py
index 0ca785d..86495a4 100644
--- a/examples/sentence_level/wmt_2020/multilingual/monotransquest.py
+++ b/examples/sentence_level/wmt_2020/multilingual/monotransquest.py
@@ -7,7 +7,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020.common.util.postprocess import format_submission
@@ -20,8 +19,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 languages = {
     "EN-DE": ["examples/sentence_level/wmt_2020/en_de/data/en-de/train.ende.df.short.tsv",
diff --git a/examples/sentence_level/wmt_2020/ne_en/monotransquest.py b/examples/sentence_level/wmt_2020/ne_en/monotransquest.py
index 6306928..8c1f929 100644
--- a/examples/sentence_level/wmt_2020/ne_en/monotransquest.py
+++ b/examples/sentence_level/wmt_2020/ne_en/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020.common.util.postprocess import format_submission
@@ -19,8 +18,7 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
+
 
 TRAIN_FILE = "examples/sentence_level/wmt_2020/ne_en/data/ne-en/train.neen.df.short.tsv"
 DEV_FILE = "examples/sentence_level/wmt_2020/ne_en/data/ne-en/dev.neen.df.short.tsv"
diff --git a/examples/sentence_level/wmt_2020/ro_en/siamesetransquest.py b/examples/sentence_level/wmt_2020/ro_en/siamesetransquest.py
index 480f75b..eadb2c0 100755
--- a/examples/sentence_level/wmt_2020/ro_en/siamesetransquest.py
+++ b/examples/sentence_level/wmt_2020/ro_en/siamesetransquest.py
@@ -8,7 +8,6 @@ import time
 
 import numpy as np
 from sklearn.model_selection import train_test_split
-from torch.utils.data import DataLoader
 
 from examples.sentence_level.wmt_2020.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020.common.util.draw import draw_scatterplot, print_stat
@@ -17,13 +16,8 @@ from examples.sentence_level.wmt_2020.common.util.postprocess import format_subm
 from examples.sentence_level.wmt_2020.common.util.reader import read_annotated_file, read_test_file
 from examples.sentence_level.wmt_2020.ro_en.siamesetransquest_config import TEMP_DIRECTORY, GOOGLE_DRIVE, DRIVE_FILE_ID, MODEL_NAME, \
     siamesetransquest_config, SEED, RESULT_FILE, RESULT_IMAGE, SUBMISSION_FILE
-from transquest.algo.sentence_level.siamesetransquest import models
 
-from transquest.algo.sentence_level.siamesetransquest.evaluation.embedding_similarity_evaluator import \
-    EmbeddingSimilarityEvaluator
 from transquest.algo.sentence_level.siamesetransquest.logging_handler import LoggingHandler
-from transquest.algo.sentence_level.siamesetransquest.losses.cosine_similarity_loss import CosineSimilarityLoss
-from transquest.algo.sentence_level.siamesetransquest.readers.input_example import InputExample
 from transquest.algo.sentence_level.siamesetransquest.run_model import SiameseTransQuestModel
 
 
@@ -76,61 +70,11 @@ if siamesetransquest_config["evaluate_during_training"]:
                     siamesetransquest_config['cache_dir']):
                 shutil.rmtree(siamesetransquest_config['cache_dir'])
 
-            os.makedirs(siamesetransquest_config['cache_dir'])
-
             train_df, eval_df = train_test_split(train, test_size=0.1, random_state=SEED * i)
-
-            # word_embedding_model = models.Transformer(MODEL_NAME, max_seq_length=siamesetransquest_config[
-            #     'max_seq_length'])
-            #
-            # pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension(),
-            #                         pooling_mode_mean_tokens=True,
-            #                         pooling_mode_cls_token=False,
-            #                         pooling_mode_max_tokens=False)
-
             model = SiameseTransQuestModel(MODEL_NAME)
-
-            train_samples = []
-            eval_samples = []
-            dev_samples = []
-            test_samples = []
-
-            for index, row in train_df.iterrows():
-                score = float(row["labels"])
-                inp_example = InputExample(texts=[row['text_a'], row['text_b']], label=score)
-                train_samples.append(inp_example)
-
-            for index, row in eval_df.iterrows():
-                score = float(row["labels"])
-                inp_example = InputExample(texts=[row['text_a'], row['text_b']], label=score)
-                eval_samples.append(inp_example)
-
-            train_dataloader = DataLoader(train_samples, shuffle=True, batch_size=siamesetransquest_config['train_batch_size'])
-            train_loss = CosineSimilarityLoss(model=model)
-
-            evaluator = EmbeddingSimilarityEvaluator.from_input_examples(eval_samples, name='eval')
-            warmup_steps = math.ceil(len(train_dataloader) * siamesetransquest_config["num_train_epochs"] * 0.1)
-
-            model.fit(train_objectives=[(train_dataloader, train_loss)],
-                      evaluator=evaluator,
-                      epochs=siamesetransquest_config['num_train_epochs'],
-                      evaluation_steps=100,
-                      optimizer_params={'lr': siamesetransquest_config["learning_rate"],
-                                        'eps': siamesetransquest_config["adam_epsilon"],
-                                        'correct_bias': False},
-                      warmup_steps=warmup_steps,
-                      output_path=siamesetransquest_config['best_model_dir'])
+            model.train_model(train_df, eval_df)
 
             model = SiameseTransQuestModel(siamesetransquest_config['best_model_dir'])
-
-            for index, row in dev.iterrows():
-                score = float(row["labels"])
-                inp_example = InputExample(texts=[row['text_a'], row['text_b']], label=score)
-                dev_samples.append(inp_example)
-
-            evaluator = EmbeddingSimilarityEvaluator.from_input_examples(dev_samples)
-            model.evaluate(evaluator,
-                           output_path=siamesetransquest_config['cache_dir'])
             dev_preds[:, i] = model.predict(dev_sentence_pairs)
             test_preds[:, i] = model.predict(test_sentence_pairs)
 
diff --git a/examples/sentence_level/wmt_2020/ro_en/siamesetransquest_config.py b/examples/sentence_level/wmt_2020/ro_en/siamesetransquest_config.py
index 3f02ade..8d346b3 100644
--- a/examples/sentence_level/wmt_2020/ro_en/siamesetransquest_config.py
+++ b/examples/sentence_level/wmt_2020/ro_en/siamesetransquest_config.py
@@ -30,13 +30,13 @@ siamesetransquest_config = {
     'max_grad_norm': 1.0,
     'do_lower_case': False,
 
-    'logging_steps': 300,
-    'save_steps': 300,
+    'logging_steps': 100,
+    'save_steps': 100,
     "no_cache": False,
     'save_model_every_epoch': True,
     'n_fold': 1,
     'evaluate_during_training': True,
-    'evaluate_during_training_steps': 300,
+    'evaluate_during_training_steps': 100,
     "evaluate_during_training_verbose": True,
     'use_cached_eval_features': False,
     'save_eval_checkpoints': True,
diff --git a/examples/sentence_level/wmt_2020/ru_en/monotransquest.py b/examples/sentence_level/wmt_2020/ru_en/monotransquest.py
index 2aa3c1a..c655077 100644
--- a/examples/sentence_level/wmt_2020/ru_en/monotransquest.py
+++ b/examples/sentence_level/wmt_2020/ru_en/monotransquest.py
@@ -6,7 +6,7 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020.common.util.download import download_from_google_drive
+
 from examples.sentence_level.wmt_2020.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020.common.util.postprocess import format_submission
@@ -19,8 +19,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FILE = "examples/sentence_level/wmt_2020/ru_en/data/ru-en/train.ruen.df.short.tsv"
 DEV_FILE = "examples/sentence_level/wmt_2020/ru_en/data/ru-en/dev.ruen.df.short.tsv"
diff --git a/examples/sentence_level/wmt_2020/si_en/monotransquest.py b/examples/sentence_level/wmt_2020/si_en/monotransquest.py
index 811ac6a..03751a0 100644
--- a/examples/sentence_level/wmt_2020/si_en/monotransquest.py
+++ b/examples/sentence_level/wmt_2020/si_en/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020.common.util.postprocess import format_submission
@@ -19,8 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FILE = "examples/sentence_level/wmt_2020/si_en/data/si-en/train.sien.df.short.tsv"
 DEV_FILE = "examples/sentence_level/wmt_2020/si_en/data/si-en/dev.sien.df.short.tsv"
diff --git a/examples/sentence_level/wmt_2020_task2/common/util/download.py b/examples/sentence_level/wmt_2020_task2/common/util/download.py
deleted file mode 100644
index feacb5a..0000000
--- a/examples/sentence_level/wmt_2020_task2/common/util/download.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from google_drive_downloader import GoogleDriveDownloader as gdd
-
-def download_from_google_drive(file_id, path):
-    gdd.download_file_from_google_drive(file_id=file_id,
-                                        dest_path= path + "/model.zip",
-                                        unzip=True)
\ No newline at end of file
diff --git a/examples/sentence_level/wmt_2020_task2/en_de/monotransquest.py b/examples/sentence_level/wmt_2020_task2/en_de/monotransquest.py
index c370e06..38aa05b 100644
--- a/examples/sentence_level/wmt_2020_task2/en_de/monotransquest.py
+++ b/examples/sentence_level/wmt_2020_task2/en_de/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020_task2.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020_task2.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020_task2.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020_task2.common.util.postprocess import format_submission
@@ -19,8 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
 
 TRAIN_FOLDER = "examples/sentence_level/wmt_2020_task2/en_de/data/en-de/train"
 DEV_FOLDER = "examples/sentence_level/wmt_2020_task2/en_de/data/en-de/dev"
diff --git a/examples/sentence_level/wmt_2020_task2/en_zh/monotransquest.py b/examples/sentence_level/wmt_2020_task2/en_zh/monotransquest.py
index 68afd3d..a463e31 100644
--- a/examples/sentence_level/wmt_2020_task2/en_zh/monotransquest.py
+++ b/examples/sentence_level/wmt_2020_task2/en_zh/monotransquest.py
@@ -6,7 +6,6 @@ import torch
 from sklearn.metrics import mean_absolute_error
 from sklearn.model_selection import train_test_split
 
-from examples.sentence_level.wmt_2020_task2.common.util.download import download_from_google_drive
 from examples.sentence_level.wmt_2020_task2.common.util.draw import draw_scatterplot, print_stat
 from examples.sentence_level.wmt_2020_task2.common.util.normalizer import fit, un_fit
 from examples.sentence_level.wmt_2020_task2.common.util.postprocess import format_submission
@@ -19,9 +18,6 @@ from transquest.algo.sentence_level.monotransquest.run_model import MonoTransQue
 if not os.path.exists(TEMP_DIRECTORY):
     os.makedirs(TEMP_DIRECTORY)
 
-if GOOGLE_DRIVE:
-    download_from_google_drive(DRIVE_FILE_ID, MODEL_NAME)
-
 TRAIN_FOLDER = "examples/sentence_level/wmt_2020_task2/en_zh/data/en-zh/train"
 DEV_FOLDER = "examples/sentence_level/wmt_2020_task2/en_zh/data/en-zh/dev"
 TEST_FOLDER = "examples/sentence_level/wmt_2020_task2/en_zh/data/en-zh/test-blind"