Feature/dynabert for multiemo

DynaBERT/data/results-dynabert-multiemo_en_all_sentence.csv

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+name,model_name,data_dir,model_dir,output_dir,model_type,task_name,max_seq_length,do_train,evaluate_during_training,do_lower_case,per_gpu_train_batch_size,per_gpu_eval_batch_size,gradient_accumulation_steps,learning_rate,weight_decay,num_train_epochs,warmup_steps,seed,hidden_dropout_prob,attention_probs_dropout_prob,data_aug,depth_mult_list,depth_lambda1,depth_lambda2,width_mult_list,width_lambda1,width_lambda2,training_phase,n_gpu,output_mode,train_batch_size,eval_batch_size,training_time,accuracy,eval_time,z_amb_precision,z_amb_recall,z_amb_f1-score,z_amb_support,z_minus_m_precision,z_minus_m_recall,z_minus_m_f1-score,z_minus_m_support,z_plus_m_precision,z_plus_m_recall,z_plus_m_f1-score,z_plus_m_support,z_zero_precision,z_zero_recall,z_zero_f1-score,z_zero_support,macro avg_precision,macro avg_recall,macro avg_f1-score,macro avg_support,weighted avg_precision,weighted avg_recall,weighted avg_f1-score,weighted avg_support,model_size,memory,parameters
+multiemo_en_all_sentence,dynabert_d_0.5_w_1.,data/multiemo2,data/models/dynabertw/multiemo_en_all_sentence,data/models/dynabert-finetuned/multiemo_en_all_sentence,bert,multiemo_en_all_sentence,128,True,True,True,16,8,1,5e-05,0.01,3.0,0,42,0.1,0.1,False,"[0.5, 0.75, 1.0]",1.0,1.0,"[0.25, 0.5, 0.75, 1.0]",1.0,0.1,final_finetuning,1,classification,16,8,34809.954543,0.7724978241949522,14.607117,0.5470219435736677,0.5124816446402349,0.5291887793783169,681,0.7953004970628107,0.8290155440414507,0.8118081180811808,2123,0.8104786545924968,0.8232588699080158,0.8168187744458931,1522,0.798219584569733,0.7582804792107117,0.7777376219732562,1419,0.737755169949677,0.7307591344501033,0.7338883234696617,5745,0.770612184792384,0.7724978241949522,0.771219156436846,5745,438020911,437941264,109485316

DynaBERT/download_bert_base.py

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+import os
+import requests
+import tarfile
+
+url = 'https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased.tar.gz'
+
+output_path = os.path.join('data', 'models')
+os.makedirs(output_path, exist_ok=True)
+
+output_tar = os.path.join(output_path, 'bert-base-uncased.tar.gz')
+model_folder = os.path.join(output_path, 'bert-base-uncased')
+
+response = requests.get(url, stream=True)
+if response.status_code == 200:
+    with open(output_tar, 'wb') as f:
+        f.write(response.raw.read())
+
+with tarfile.open(name=output_tar, mode="r|gz") as tar_ref:
+    tar_ref.extractall(model_folder)
+
+os.rename(os.path.join(model_folder, 'bert_config.json'), os.path.join(model_folder, 'config.json'))
+
+os.remove(output_tar)
+
+url_vocab = 'https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt'
+r = requests.get(url_vocab)
+
+with open(os.path.join(model_folder, 'vocab.txt'), 'wb') as f:
+    f.write(r.content)
+
+print('Completed!')