diff --git "a/run.log" "b/run.log" new file mode 100644--- /dev/null +++ "b/run.log" @@ -0,0 +1,27233 @@ +12/16/2021 16:19:08 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 4distributed training: False, 16-bits training: False +12/16/2021 16:19:08 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments( +_n_gpu=4, +adafactor=True, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +bf16=False, +bf16_full_eval=False, +dataloader_drop_last=False, +dataloader_num_workers=0, +dataloader_pin_memory=True, +ddp_find_unused_parameters=None, +debug=[], +deepspeed=None, +disable_tqdm=False, +do_eval=True, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_steps=1000, +evaluation_strategy=IntervalStrategy.STEPS, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +generation_max_length=None, +generation_num_beams=None, +gradient_accumulation_steps=1, +gradient_checkpointing=False, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_model_id=None, +hub_strategy=HubStrategy.EVERY_SAVE, +hub_token=, +ignore_data_skip=False, +label_names=None, +label_smoothing_factor=0.1, +learning_rate=0.0002, +length_column_name=length, +load_best_model_at_end=False, +local_rank=-1, +log_level=-1, +log_level_replica=-1, +log_on_each_node=True, +logging_dir=/data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/runs/Dec16_16-19-08_csr-dgx1-04, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=1, +logging_strategy=IntervalStrategy.STEPS, +lr_scheduler_type=SchedulerType.LINEAR, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +no_cuda=False, +num_train_epochs=10.0, +output_dir=/data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1, +overwrite_output_dir=True, +past_index=-1, +per_device_eval_batch_size=2, +per_device_train_batch_size=2, +predict_with_generate=False, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +remove_unused_columns=True, +report_to=['wandb'], +resume_from_checkpoint=None, +run_name=pegasus-billsum-10eph-run1, +save_on_each_node=False, +save_steps=2000, +save_strategy=IntervalStrategy.STEPS, +save_total_limit=None, +seed=42, +sharded_ddp=[], +skip_memory_metrics=True, +sortish_sampler=False, +tf32=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_legacy_prediction_loop=False, +warmup_ratio=0.0, +warmup_steps=0, +weight_decay=0.0, +xpu_backend=None, +) +12/16/2021 16:19:09 - WARNING - datasets.builder - Using custom data configuration default +12/16/2021 16:19:09 - INFO - datasets.info - Loading Dataset Infos from /data1/vchua/.cache/huggingface/modules/datasets_modules/datasets/billsum/d1e95173aed3acb71327864be74ead49b578522e4c7206048b2f2e5351b57959 +12/16/2021 16:19:09 - INFO - datasets.builder - Overwrite dataset info from restored data version. +12/16/2021 16:19:09 - INFO - datasets.info - Loading Dataset info from /data1/vchua/.cache/huggingface/datasets/billsum/default/3.0.0/d1e95173aed3acb71327864be74ead49b578522e4c7206048b2f2e5351b57959 +12/16/2021 16:19:09 - WARNING - datasets.builder - Reusing dataset billsum (/data1/vchua/.cache/huggingface/datasets/billsum/default/3.0.0/d1e95173aed3acb71327864be74ead49b578522e4c7206048b2f2e5351b57959) +12/16/2021 16:19:09 - INFO - datasets.info - Loading Dataset info from /data1/vchua/.cache/huggingface/datasets/billsum/default/3.0.0/d1e95173aed3acb71327864be74ead49b578522e4c7206048b2f2e5351b57959 + 0%| | 0/3 [00:00> loading configuration file https://huggingface.co/google/pegasus-large/resolve/main/config.json from cache at /data1/vchua/.cache/huggingface/transformers/3fa0446657dd3714a950ba400a3fa72686d0f815da436514e4823a973ef23e20.f2dc0735a07d1a70170e8e0e4d5fb57ad90d8ea5201a0dbd4b33f2f499444852 +[INFO|configuration_utils.py:641] 2021-12-16 16:19:11,478 >> Model config PegasusConfig { + "_name_or_path": "google/pegasus-large", + "activation_dropout": 0.1, + "activation_function": "relu", + "add_bias_logits": false, + "add_final_layer_norm": true, + "architectures": [ + "PegasusForConditionalGeneration" + ], + "attention_dropout": 0.1, + "bos_token_id": 0, + "classif_dropout": 0.0, + "classifier_dropout": 0.0, + "d_model": 1024, + "decoder_attention_heads": 16, + "decoder_ffn_dim": 4096, + "decoder_layerdrop": 0.0, + "decoder_layers": 16, + "decoder_start_token_id": 0, + "dropout": 0.1, + "encoder_attention_heads": 16, + "encoder_ffn_dim": 4096, + "encoder_layerdrop": 0.0, + "encoder_layers": 16, + "eos_token_id": 1, + "extra_pos_embeddings": 1, + "force_bos_token_to_be_generated": false, + "forced_eos_token_id": 1, + "gradient_checkpointing": false, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1", + "2": "LABEL_2" + }, + "init_std": 0.02, + "is_encoder_decoder": true, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1, + "LABEL_2": 2 + }, + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024, + "model_type": "pegasus", + "normalize_before": true, + "normalize_embedding": false, + "num_beams": 8, + "num_hidden_layers": 16, + "pad_token_id": 0, + "scale_embedding": true, + "static_position_embeddings": true, + "task_specific_params": { + "summarization_aeslc": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 512 + }, + "summarization_arxiv": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_big_patent": { + "length_penalty": 0.7, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_billsum": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_cnn_dailymail": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 1024 + }, + "summarization_gigaword": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 128 + }, + "summarization_large": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_multi_news": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_newsroom": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_pubmed": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_reddit_tifu": { + "length_penalty": 0.6, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_wikihow": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 512 + }, + "summarization_xsum": { + "length_penalty": 0.8, + "max_length": 64, + "max_position_embeddings": 512 + } + }, + "transformers_version": "4.13.0", + "use_cache": true, + "vocab_size": 96103 +} + +[INFO|configuration_utils.py:604] 2021-12-16 16:19:12,532 >> loading configuration file https://huggingface.co/google/pegasus-large/resolve/main/config.json from cache at /data1/vchua/.cache/huggingface/transformers/3fa0446657dd3714a950ba400a3fa72686d0f815da436514e4823a973ef23e20.f2dc0735a07d1a70170e8e0e4d5fb57ad90d8ea5201a0dbd4b33f2f499444852 +[INFO|configuration_utils.py:641] 2021-12-16 16:19:12,533 >> Model config PegasusConfig { + "_name_or_path": "google/pegasus-large", + "activation_dropout": 0.1, + "activation_function": "relu", + "add_bias_logits": false, + "add_final_layer_norm": true, + "architectures": [ + "PegasusForConditionalGeneration" + ], + "attention_dropout": 0.1, + "bos_token_id": 0, + "classif_dropout": 0.0, + "classifier_dropout": 0.0, + "d_model": 1024, + "decoder_attention_heads": 16, + "decoder_ffn_dim": 4096, + "decoder_layerdrop": 0.0, + "decoder_layers": 16, + "decoder_start_token_id": 0, + "dropout": 0.1, + "encoder_attention_heads": 16, + "encoder_ffn_dim": 4096, + "encoder_layerdrop": 0.0, + "encoder_layers": 16, + "eos_token_id": 1, + "extra_pos_embeddings": 1, + "force_bos_token_to_be_generated": false, + "forced_eos_token_id": 1, + "gradient_checkpointing": false, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1", + "2": "LABEL_2" + }, + "init_std": 0.02, + "is_encoder_decoder": true, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1, + "LABEL_2": 2 + }, + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024, + "model_type": "pegasus", + "normalize_before": true, + "normalize_embedding": false, + "num_beams": 8, + "num_hidden_layers": 16, + "pad_token_id": 0, + "scale_embedding": true, + "static_position_embeddings": true, + "task_specific_params": { + "summarization_aeslc": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 512 + }, + "summarization_arxiv": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_big_patent": { + "length_penalty": 0.7, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_billsum": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_cnn_dailymail": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 1024 + }, + "summarization_gigaword": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 128 + }, + "summarization_large": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_multi_news": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_newsroom": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_pubmed": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_reddit_tifu": { + "length_penalty": 0.6, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_wikihow": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 512 + }, + "summarization_xsum": { + "length_penalty": 0.8, + "max_length": 64, + "max_position_embeddings": 512 + } + }, + "transformers_version": "4.13.0", + "use_cache": true, + "vocab_size": 96103 +} + +[INFO|tokenization_utils_base.py:1742] 2021-12-16 16:19:14,625 >> loading file https://huggingface.co/google/pegasus-large/resolve/main/spiece.model from cache at /data1/vchua/.cache/huggingface/transformers/66f187d645734a6204f3fd24593fbf0d9e36b528dd85b3adae9a566b17b4768f.1acf68c74589da6c7fa3548093824dfc450a54637f4356929bbfea7e294a68f8 +[INFO|tokenization_utils_base.py:1742] 2021-12-16 16:19:14,625 >> loading file https://huggingface.co/google/pegasus-large/resolve/main/tokenizer.json from cache at None +[INFO|tokenization_utils_base.py:1742] 2021-12-16 16:19:14,625 >> loading file https://huggingface.co/google/pegasus-large/resolve/main/added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:1742] 2021-12-16 16:19:14,626 >> loading file https://huggingface.co/google/pegasus-large/resolve/main/special_tokens_map.json from cache at /data1/vchua/.cache/huggingface/transformers/fbf9c7cf2d49b24712b53a2760e7c62a2acecd1496908822df00b8ec2683ca6d.294ebaa4cd17bb284635004c92d2c4d522ec488c828dcce0c2471b6f28e3fe82 +[INFO|tokenization_utils_base.py:1742] 2021-12-16 16:19:14,626 >> loading file https://huggingface.co/google/pegasus-large/resolve/main/tokenizer_config.json from cache at /data1/vchua/.cache/huggingface/transformers/74256fafbb3cb536e351e6731914d42f732e77d33e537b6c19fb72f4b74f50ea.43f396f0ee3b974f9128267d49f69a26b11f3ed290851ac5788a549cc2979671 +[INFO|configuration_utils.py:604] 2021-12-16 16:19:15,336 >> loading configuration file https://huggingface.co/google/pegasus-large/resolve/main/config.json from cache at /data1/vchua/.cache/huggingface/transformers/3fa0446657dd3714a950ba400a3fa72686d0f815da436514e4823a973ef23e20.f2dc0735a07d1a70170e8e0e4d5fb57ad90d8ea5201a0dbd4b33f2f499444852 +[INFO|configuration_utils.py:641] 2021-12-16 16:19:15,339 >> Model config PegasusConfig { + "_name_or_path": "google/pegasus-large", + "activation_dropout": 0.1, + "activation_function": "relu", + "add_bias_logits": false, + "add_final_layer_norm": true, + "architectures": [ + "PegasusForConditionalGeneration" + ], + "attention_dropout": 0.1, + "bos_token_id": 0, + "classif_dropout": 0.0, + "classifier_dropout": 0.0, + "d_model": 1024, + "decoder_attention_heads": 16, + "decoder_ffn_dim": 4096, + "decoder_layerdrop": 0.0, + "decoder_layers": 16, + "decoder_start_token_id": 0, + "dropout": 0.1, + "encoder_attention_heads": 16, + "encoder_ffn_dim": 4096, + "encoder_layerdrop": 0.0, + "encoder_layers": 16, + "eos_token_id": 1, + "extra_pos_embeddings": 1, + "force_bos_token_to_be_generated": false, + "forced_eos_token_id": 1, + "gradient_checkpointing": false, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1", + "2": "LABEL_2" + }, + "init_std": 0.02, + "is_encoder_decoder": true, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1, + "LABEL_2": 2 + }, + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024, + "model_type": "pegasus", + "normalize_before": true, + "normalize_embedding": false, + "num_beams": 8, + "num_hidden_layers": 16, + "pad_token_id": 0, + "scale_embedding": true, + "static_position_embeddings": true, + "task_specific_params": { + "summarization_aeslc": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 512 + }, + "summarization_arxiv": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_big_patent": { + "length_penalty": 0.7, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_billsum": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_cnn_dailymail": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 1024 + }, + "summarization_gigaword": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 128 + }, + "summarization_large": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_multi_news": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_newsroom": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_pubmed": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_reddit_tifu": { + "length_penalty": 0.6, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_wikihow": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 512 + }, + "summarization_xsum": { + "length_penalty": 0.8, + "max_length": 64, + "max_position_embeddings": 512 + } + }, + "transformers_version": "4.13.0", + "use_cache": true, + "vocab_size": 96103 +} + +[INFO|configuration_utils.py:604] 2021-12-16 16:19:16,215 >> loading configuration file https://huggingface.co/google/pegasus-large/resolve/main/config.json from cache at /data1/vchua/.cache/huggingface/transformers/3fa0446657dd3714a950ba400a3fa72686d0f815da436514e4823a973ef23e20.f2dc0735a07d1a70170e8e0e4d5fb57ad90d8ea5201a0dbd4b33f2f499444852 +[INFO|configuration_utils.py:641] 2021-12-16 16:19:16,217 >> Model config PegasusConfig { + "_name_or_path": "google/pegasus-large", + "activation_dropout": 0.1, + "activation_function": "relu", + "add_bias_logits": false, + "add_final_layer_norm": true, + "architectures": [ + "PegasusForConditionalGeneration" + ], + "attention_dropout": 0.1, + "bos_token_id": 0, + "classif_dropout": 0.0, + "classifier_dropout": 0.0, + "d_model": 1024, + "decoder_attention_heads": 16, + "decoder_ffn_dim": 4096, + "decoder_layerdrop": 0.0, + "decoder_layers": 16, + "decoder_start_token_id": 0, + "dropout": 0.1, + "encoder_attention_heads": 16, + "encoder_ffn_dim": 4096, + "encoder_layerdrop": 0.0, + "encoder_layers": 16, + "eos_token_id": 1, + "extra_pos_embeddings": 1, + "force_bos_token_to_be_generated": false, + "forced_eos_token_id": 1, + "gradient_checkpointing": false, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1", + "2": "LABEL_2" + }, + "init_std": 0.02, + "is_encoder_decoder": true, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1, + "LABEL_2": 2 + }, + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024, + "model_type": "pegasus", + "normalize_before": true, + "normalize_embedding": false, + "num_beams": 8, + "num_hidden_layers": 16, + "pad_token_id": 0, + "scale_embedding": true, + "static_position_embeddings": true, + "task_specific_params": { + "summarization_aeslc": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 512 + }, + "summarization_arxiv": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_big_patent": { + "length_penalty": 0.7, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_billsum": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_cnn_dailymail": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 1024 + }, + "summarization_gigaword": { + "length_penalty": 0.6, + "max_length": 32, + "max_position_embeddings": 128 + }, + "summarization_large": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_multi_news": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_newsroom": { + "length_penalty": 0.8, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_pubmed": { + "length_penalty": 0.8, + "max_length": 256, + "max_position_embeddings": 1024 + }, + "summarization_reddit_tifu": { + "length_penalty": 0.6, + "max_length": 128, + "max_position_embeddings": 512 + }, + "summarization_wikihow": { + "length_penalty": 0.6, + "max_length": 256, + "max_position_embeddings": 512 + }, + "summarization_xsum": { + "length_penalty": 0.8, + "max_length": 64, + "max_position_embeddings": 512 + } + }, + "transformers_version": "4.13.0", + "use_cache": true, + "vocab_size": 96103 +} + +[INFO|modeling_utils.py:1352] 2021-12-16 16:19:16,942 >> loading weights file https://huggingface.co/google/pegasus-large/resolve/main/pytorch_model.bin from cache at /data1/vchua/.cache/huggingface/transformers/ef3a8274e003ba4d3ae63f2728378e73affec0029e797c0bbb80be8856130c4f.a99cb24bd92c7087e95d96a1c3eb660b51e498705f8bd068a58c69c20616f514 +[INFO|modeling_utils.py:1619] 2021-12-16 16:19:30,923 >> All model checkpoint weights were used when initializing PegasusForConditionalGeneration. + +[INFO|modeling_utils.py:1627] 2021-12-16 16:19:30,924 >> All the weights of PegasusForConditionalGeneration were initialized from the model checkpoint at google/pegasus-large. +If your task is similar to the task the model of the checkpoint was trained on, you can already use PegasusForConditionalGeneration for predictions without further training. + Running tokenizer on train dataset: 0%| | 0/18 [00:00> ***** Running training ***** +[INFO|trainer.py:1205] 2021-12-16 16:19:54,366 >> Num examples = 17054 +[INFO|trainer.py:1206] 2021-12-16 16:19:54,366 >> Num Epochs = 10 +[INFO|trainer.py:1207] 2021-12-16 16:19:54,366 >> Instantaneous batch size per device = 2 +[INFO|trainer.py:1208] 2021-12-16 16:19:54,366 >> Total train batch size (w. parallel, distributed & accumulation) = 8 +[INFO|trainer.py:1209] 2021-12-16 16:19:54,366 >> Gradient Accumulation steps = 1 +[INFO|trainer.py:1210] 2021-12-16 16:19:54,366 >> Total optimization steps = 21320 +[INFO|integrations.py:502] 2021-12-16 16:19:54,368 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true" +huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks... +To disable this warning, you can either: + - Avoid using `tokenizers` before the fork if possible + - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false) +wandb: Currently logged in as: vchua (use `wandb login --relogin` to force relogin) +huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks... +To disable this warning, you can either: + - Avoid using `tokenizers` before the fork if possible + - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false) +huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks... +To disable this warning, you can either: + - Avoid using `tokenizers` before the fork if possible + - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false) +huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks... +To disable this warning, you can either: + - Avoid using `tokenizers` before the fork if possible + - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false) +wandb: wandb version 0.12.8 is available! To upgrade, please run: +wandb: $ pip install wandb --upgrade +wandb: Tracking run with wandb version 0.12.7 +wandb: Syncing run pegasus-billsum-10eph-run1 +wandb: View project at https://wandb.ai/vchua/csr-dgx1-04_pegasus_ft +wandb: View run at https://wandb.ai/vchua/csr-dgx1-04_pegasus_ft/runs/3c10akuv +wandb: Run data is saved locally in /data1/vchua/dgx4-pegasus-hf4p13/transformers/examples/pytorch/summarization/wandb/run-20211216_161954-3c10akuv +wandb: Run `wandb offline` to turn off syncing. + + 0% 0/21320 [00:00> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 16:33:54,102 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 16:33:54,102 >> Batch size = 8 +{'loss': 2.9951, 'learning_rate': 0.00019154784240150093, 'epoch': 0.42} +{'loss': 2.8947, 'learning_rate': 0.00019153846153846155, 'epoch': 0.42} +{'loss': 2.7301, 'learning_rate': 0.00019152908067542214, 'epoch': 0.42} +{'loss': 2.8416, 'learning_rate': 0.00019151969981238276, 'epoch': 0.42} +{'loss': 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/data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-2000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 16:50:01,816 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-2000/special_tokens_map.json + 9% 2001/21320 [30:06<117:46:05, 21.95s/it] 9% 2001/21320 [30:06<117:46:05, 21.95s/it] 9% 2002/21320 [30:07<83:52:09, 15.63s/it] 9% 2002/21320 [30:07<83:52:09, 15.63s/it] 9% 2003/21320 [30:07<59:58:29, 11.18s/it] 9% 2003/21320 [30:07<59:58:29, 11.18s/it] 9% 2004/21320 [30:08<43:16:39, 8.07s/it] 9% 2004/21320 [30:08<43:16:39, 8.07s/it] 9% 2005/21320 [30:09<31:34:52, 5.89s/it] 9% 2005/21320 [30:09<31:34:52, 5.89s/it] 9% 2006/21320 [30:10<23:24:36, 4.36s/it] 9% 2006/21320 [30:10<23:24:36, 4.36s/it] 9% 2007/21320 [30:11<17:41:14, 3.30s/it] 9% 2007/21320 [30:11<17:41:14, 3.30s/it] 9% 2008/21320 [30:11<13:39:53, 2.55s/it] 9% 2008/21320 [30:11<13:39:53, 2.55s/it] 9% 2009/21320 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Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 17:03:52,993 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 17:03:52,994 >> Batch size = 8 + +{'loss': 2.6868, 'learning_rate': 0.0001728048780487805, 'epoch': 1.36} +{'loss': 2.5498, 'learning_rate': 0.00017279549718574112, 'epoch': 1.36} +{'loss': 3.1252, 'learning_rate': 0.00017278611632270168, 'epoch': 1.36} +{'loss': 2.9791, 'learning_rate': 0.00017277673545966227, 'epoch': 1.36} +{'loss': 2.8496, 'learning_rate': 0.0001727673545966229, 'epoch': 1.36} +{'loss': 2.7805, 'learning_rate': 0.00017275797373358348, 'epoch': 1.36} +{'loss': 2.5874, 'learning_rate': 0.0001727485928705441, 'epoch': 1.36} +{'loss': 2.657, 'learning_rate': 0.0001727392120075047, 'epoch': 1.36} +{'loss': 2.886, 'learning_rate': 0.0001727298311444653, 'epoch': 1.36} +{'loss': 2.8002, 'learning_rate': 0.0001727204502814259, 'epoch': 1.36} +{'loss': 2.875, 'learning_rate': 0.00017271106941838652, 'epoch': 1.36} +{'loss': 2.7533, 'learning_rate': 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+{'loss': 2.4897, 'learning_rate': 0.00017231707317073172, 'epoch': 1.38} +{'loss': 2.7466, 'learning_rate': 0.00017230769230769234, 'epoch': 1.38} +{'loss': 2.5751, 'learning_rate': 0.00017229831144465293, 'epoch': 1.39} +{'loss': 2.5717, 'learning_rate': 0.00017228893058161352, 'epo 0% 0/237 [00:00> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 17:18:53,877 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 17:18:53,877 >> Batch size = 8 +{'loss': 2.6393, 'learning_rate': 0.00016343339587242029, 'epoch': 1.83} +{'loss': 2.8644, 'learning_rate': 0.00016342401500938088, 'epoch': 1.83} +{'loss': 2.644, 'learning_rate': 0.00016341463414634147, 'epoch': 1.83} +{'loss': 2.7478, 'learning_rate': 0.00016340525328330209, 'epoch': 1.83} +{'loss': 2.5842, 'learning_rate': 0.00016339587242026268, 'epoch': 1.83} +{'loss': 2.9765, 'learning_rate': 0.00016338649155722327, 'epoch': 1.83} +{'loss': 2.5882, 'learning_rate': 0.00016337711069418386, 'epoch': 1.83} +{'loss': 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+{'loss': 2.6171, 'learning_rate': 0.00016311444652908068, 'epoch': 1.84} +{'loss': 2.7688, 'learning_rate': 0.0001631050656660413, 'epoch': 1.84} +{'loss': 2.7053, 'learning_rate': 0.00016309568480300188, 'epoch': 1.85} +{'loss': 2.5286, 'learning_rate': 0.0001630863039399625, 'epoch': 1.85} +{'loss': 2.9101, 'learning_rate': 0.0001630769230769231, 'epoch': 1.85} +{'loss': 2.4861, 'learning_rate': 0.00016306754221388368, 'epoch': 1.85} +{'loss': 2.9975, 'learning_rate': 0.00016305816135084428, 'epoch': 1.85} +{'loss': 2.5152, 'learning_rate': 0.00016304878048780487, 'epoch': 1.85} +{'loss': 2.5568, 'learning_rate': 0.00016303939962476548, 'epoch': 1.85} +{'loss': 2.856, 'learning_rate': 0.00016303001876172608, 'epoch': 1.85} +{'loss': 2.5329, 'learning_rate': 0.0001630206378986867, 'epoch': 1.85} +{'loss': 2.7329, 'learning_rate': 0.00016301125703564728, 'epoch': 1.85} +{'loss': 2.5559, 'learning_rate': 0.0001630018761726079, 'epoch': 1.85} +{'loss': 2.6716, 'learning_rate': 0.0001629924953095685, 'epoch': 1.85} +{'loss': 2.5884, 'learning_rate': 0.00016298311444652908, 'epoch': 1.85} +{'loss': 2.4214, 'learning_rate': 0.00016297373358348968, 'epoch': 1.85} +{'loss': 2.934, 'learning_rate': 0.0001629643527204503, 'epoch': 1.85} +{'loss': 2.7265, 'learning_rate': 0.00016295497185741088, 'epoch': 1.85} +{'loss': 2.7268, 'learning_rate': 0.0001629455909943715, 'epoch': 1.85} +{'loss': 2.4822, 'learning_rate': 0.0001629362101313321, 'epoch': 1.85} +{'loss': 2.5917, 'learning_rate': 0.00016292682926829268, 'epoch': 1.85} +{'loss': 2.8121, 'learning_rate': 0.000162917 + 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-4000 +[INFO|configuration_utils.py:425] 2021-12-16 17:20:01,622 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-4000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 17:20:04,431 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-4000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 17:20:04,432 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-4000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 17:20:04,432 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-4000/special_tokens_map.json + 19% 4001/21320 [1:00:08<106:10:44, 22.07s/it] 19% 4001/21320 [1:00:08<106:10:44, 22.07s/it] 19% 4002/21320 [1:00:09<75:28:59, 15.69s/it] 19% 4002/21320 [1:00:09<75:28:59, 15.69s/it] 19% 4003/21320 [1:00:10<54:00:51, 11.23s/it] 19% 4003/21320 [1:00:10<54:00:51, 11.23s/it] 19% 4004/21320 [1:00:11<38:56:16, 8.10s/it] 19% 4004/21320 [1:00:11<38:56:16, 8.10s/it] 19% 4005/21320 [1:00:11<28:25:05, 5.91s/it] 19% 4005/21320 [1:00:11<28:25:05, 5.91s/it] 19% 4006/21320 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[1:13:54<3:40:48, 1.23it/s] 23% 4991/21320 [1:13:55<3:47:40, 1.20it/s] 23% 4991/21320 [1:13:55<3:47:40, 1.20it/s] 23% 4992/21320 [1:13:56<3:47:44, 1.19it/s] 23% 4992/21320 [1:13:56<3:47:44, 1.19it/s] 23% 4993/21320 [1:13:57<3:49:33, 1.19it/s] 23% 4993/21320 [1:13:57<3:49:33, 1.19it/s] 23% 4994/21320 [1:13:58<3:51:20, 1.18it/s] 23% 4994/21320 [1:13:58<3:51:20, 1.18it/s] 23% 4995/21320 [1:13:58<3:47:04, 1.20it/s] 23% 4995/21320 [1:13:58<3:47:04, 1.20it/s] 23% 4996/21320 [1:13:59<3:47:35, 1.20it/s] 23% 4996/21320 [1:13:59<3:47:35, 1.20it/s] 23% 4997/21320 [1:14:00<3:46:31, 1.20it/s] 23% 4997/21320 [1:14:00<3:46:31, 1.20it/s] 23% 4998/21320 [1:14:01<3:42:59, 1.22it/s] 23% 4998/21320 [1:14:01<3:42:59, 1.22it/s] 23% 4999/21320 [1:14:02<3:40:51, 1.23it/s] 23% 4999/21320 [1:14:02<3:40:51, 1.23it/s] 23% 5000/21320 [1:14:02<3:40:03, 1.24it/s] 23% 5000/21320 [1:14:02<3:40:03, 1.24it/s][INFO|trainer.py:2281] 2021-12-16 17:33:59,677 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 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2.7421, 'learning_rate': 0.00014387429643527205, 'epoch': 2.81} +{'loss': 2.4147, 'learning_rate': 0.00014386491557223264, 'epoch': 2.81} +{'loss': 2.6461, 'learning_rate': 0.00014385553470919326, 'epoch': 2.81} +{'loss': 2.2413, 'learning_rate': 0.00014384615384615385, 'epoch': 2.81} +{'loss': 2.635, 'learning_rate': 0.00014383677298311444, 'epoch': 2.81} +{'loss': 2.5204, 'learning_rate': 0.00014382739212007506, 'epoch': 2.81} +{'loss': 2.5139, 'learning_rate': 0.00014381801125703565, 'epoch': 2.81} +{'loss': 2.6605, 'learning_rate': 0.00014380863039399627, 'epoch': 2.81} +{'loss': 2.4119, 'learning_rate': 0.00014379924953095686, 'epoch': 2.81} +{'loss': 2.6751, 'learning_rate': 0.00014378986866791745, 'epoch': 2.81} +{'loss': 2.5118, 'learning_rate': 0.00014378048780487804, 'epoch': 2.81} +{'loss': 2.7012, 'learning_rate': 0.00014377110694183866, 'epoch': 2.81} +{'loss': 2.5069, 'learning_rate': 0.00014376172607879925, 'epoch': 2.81} +{'loss': 2.6769, 'learning_rate': 0.00014375234521575987, 'epoch': 2.81} +{'loss': 2.44, 'learning_rate': 0.00014374296435272046, 'epoch': 2.81} +{'loss': 2.4644, 'learning_rate': 0.00014373358348968108, 'epoch': 2.81} +{'loss': 2.5583, 'learning_rate': 0.00014372420262664167, 'epoch': 2.81} +{'loss': 2.5505, 'learning_rate': 0.00014371482176360226, 'epoch': 2.81} + 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-6000 +[INFO|configuration_utils.py:425] 2021-12-16 17:50:09,755 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-6000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 17:50:12,557 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-6000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 17:50:12,558 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-6000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 17:50:12,558 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-6000/special_tokens_map.json + 28% 6001/21320 [1:30:16<93:53:41, 22.07s/it] 28% 6001/21320 [1:30:16<93:53:41, 22.07s/it] 28% 6002/21320 [1:30:17<66:47:13, 15.70s/it] 28% 6002/21320 [1:30:17<66:47:13, 15.70s/it] 28% 6003/21320 [1:30:18<47:46:30, 11.23s/it] 28% 6003/21320 [1:30:18<47:46:30, 11.23s/it] 28% 6004/21320 [1:30:19<34:27:43, 8.10s/it] 28% 6004/21320 [1:30:19<34:27:43, 8.10s/it] 28% 6005/21320 [1:30:20<25:08:04, 5.91s/it] 28% 6005/21320 [1:30:20<25:08:04, 5.91s/it] 28% 6006/21320 [1:30:21<18:41:45, 4.40s/it] 28% 6006/21320 [1:30:21<18:41:45, 4.40s/it] 28% 6007/21320 [1:30:21<14:06:28, 3.32s/it] 28% 6007/21320 [1:30:21<14:06:28, 3.32s/it] 28% 6008/21320 [1:30:22<10:53:24, 2.56s/it] 28% 6008/21320 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[1:43:59<3:25:03, 1.16it/s] 33% 6993/21320 [1:43:59<3:25:03, 1.16it/s] 33% 6994/21320 [1:44:00<3:25:38, 1.16it/s] 33% 6994/21320 [1:44:00<3:25:38, 1.16it/s] 33% 6995/21320 [1:44:01<3:25:40, 1.16it/s] 33% 6995/21320 [1:44:01<3:25:40, 1.16it/s] 33% 6996/21320 [1:44:02<3:25:02, 1.16it/s] 33% 6996/21320 [1:44:02<3:25:02, 1.16it/s] 33% 6997/21320 [1:44:03<3:26:07, 1.16it/s] 33% 6997/21320 [1:44:03<3:26:07, 1.16it/s] 33% 6998/21320 [1:44:04<3:27:42, 1.15it/s] 33% 6998/21320 [1:44:04<3:27:42, 1.15it/s] 33% 6999/21320 [1:44:05<3:25:22, 1.16it/s] 33% 6999/21320 [1:44:05<3:25:22, 1.16it/s] 33% 7000/21320 [1:44:05<3:25:18, 1.16it/s] 33% 7000/21320 [1:44:05<3:25:18, 1.16it/s][INFO|trainer.py:2281] 2021-12-16 18:04:02,668 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 18:04:02,668 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 18:04:02,669 >> Batch size = 8 + +{'loss': 2.3845, 'learning_rate': 0.000135281425891182, 'epoch': 3.24} +{'loss': 2.3826, 'learning_rate': 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0.00012542213883677298, 'epoch': 3.73} +{'loss': 2.4796, 'learning_rate': 0.0001254127579737336, 'epoch': 3.73} +{'loss': 2.7394, 'learning_rate': 0.00012540337711069419, 'epoch': 3.73} +{'loss': 2.5717, 'learning_rate': 0.0001253939962476548, 'epoch': 3.73} +{'loss': 2.3552, 'learning_rate': 0.00012538461538 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-8000 +[INFO|configuration_utils.py:425] 2021-12-16 18:20:12,579 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-8000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 18:20:15,389 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-8000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 18:20:15,390 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-8000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 18:20:15,390 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-8000/special_tokens_map.json + 38% 8001/21320 [2:00:19<81:43:45, 22.09s/it] 38% 8001/21320 [2:00:19<81:43:45, 22.09s/it] 38% 8002/21320 [2:00:20<58:05:49, 15.70s/it] 38% 8002/21320 [2:00:20<58:05:49, 15.70s/it] 38% 8003/21320 [2:00:21<41:32:46, 11.23s/it] 38% 8003/21320 [2:00:21<41:32:46, 11.23s/it] 38% 8004/21320 [2:00:22<29:58:17, 8.10s/it] 38% 8004/21320 [2:00:22<29:58:17, 8.10s/it] 38% 8005/21320 [2:00:23<21:51:59, 5.91s/it] 38% 8005/21320 [2:00:23<21:51:59, 5.91s/it] 38% 8006/21320 [2:00:23<16:17:50, 4.41s/it] 38% 8006/21320 [2:00:23<16:17:50, 4.41s/it] 38% 8007/21320 [2:00:24<12:18:57, 3.33s/it] 38% 8007/21320 [2:00:24<12:18:57, 3.33s/it] 38% 8008/21320 [2:00:25<9:30:38, 2.57s/it] 38% 8008/21320 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[2:14:06<2:49:40, 1.21it/s] 42% 8993/21320 [2:14:07<2:54:38, 1.18it/s] 42% 8993/21320 [2:14:07<2:54:38, 1.18it/s] 42% 8994/21320 [2:14:08<2:55:56, 1.17it/s] 42% 8994/21320 [2:14:08<2:55:56, 1.17it/s] 42% 8995/21320 [2:14:08<2:54:01, 1.18it/s] 42% 8995/21320 [2:14:08<2:54:01, 1.18it/s] 42% 8996/21320 [2:14:09<2:51:43, 1.20it/s] 42% 8996/21320 [2:14:09<2:51:43, 1.20it/s] 42% 8997/21320 [2:14:10<2:49:23, 1.21it/s] 42% 8997/21320 [2:14:10<2:49:23, 1.21it/s] 42% 8998/21320 [2:14:11<2:54:40, 1.18it/s] 42% 8998/21320 [2:14:11<2:54:40, 1.18it/s] 42% 8999/21320 [2:14:12<2:54:56, 1.17it/s] 42% 8999/21320 [2:14:12<2:54:56, 1.17it/s] 42% 9000/21320 [2:14:13<2:53:52, 1.18it/s] 42% 9000/21320 [2:14:13<2:53:52, 1.18it/s][INFO|trainer.py:2281] 2021-12-16 18:34:09,864 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 18:34:09,864 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 18:34:09,864 >> Batch size = 8 + +{'loss': 2.3554, 'learning_rate': 0.00011651969981238275, 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+{'loss': 2.4783, 'learning_rate': 0.00011613508442776737, 'epoch': 4.19} +{'loss': 2.3428, 'learning_rate': 0.00011612570356472797, 'epoch': 4.19} +{'loss': 2.3743, 'learning_rate': 0.00011611632270168856, 'epoch': 4.19} +{'loss': 2.3614, 'learning_rate': 0.00011610694183864916, 'epoch': 4.19} +{'loss': 2.2623, 'learning_rate': 0.00011609756097560975, 'epoch': 4.2} +{'loss': 2.6701, 'learning_rate': 0.00011608818011257037, 'epoch': 4.2} +{'loss': 2.3509, 'learning_rate': 0.00011607879924953096, 'epoch': 4.2} +{'loss': 2.5193, 'learning_rate': 0.00011606941838649157, 'epoch': 4.2} +{'loss': 2.5042, 'learning_rate': 0.00011606003752345216, 'epoch': 4.2} +{'loss': 2.4002, 'learning_rate': 0.00011605065666041277, 'epoch': 4.2} +{'loss': 2.6145, 'learning_rate': 0.00011604127579737337, 'epoch': 4.2} +{'loss': 2.3661, 'learning_rate': 0.00011603189493433397, 'epoch': 4.2} +{'loss': 2.725, 'learning_rate': 0.00011602251407129456, 'epoch': 4.2} +{'loss': 2.2954, 'learning_rate': 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+{'loss': 2.3327, 'learning_rate': 0.00010681050656660414, 'epoch': 4.66} +{'loss': 2.4863, 'learning_rate': 0.00010680112570356473, 'epoch': 4.66} +{'loss': 2.4778, 'learning_rate': 0.00010679174484052535, 'epoch': 4.66} +{'loss': 2.4881, 'learning_rate': 0.00010678236397748594, 'epoch': 4.66} +{'loss': 2.5259, 'learning_rate': 0.00010677298311444653, 'epoch': 4.66} +{'loss': 2.5259, 'learning_rate': 0.00010676360225140713, 'epoch': 4.66} +{'loss': 2.2445, 'learning_rate': 0.00010675422138836772, 'epoch': 4.66} +{'loss': 2.4778, 'learning_rate': 0.00010674484052532834, 'epoch': 4.66} +{'loss': 2.4695, 'learning_rate': 0.00010673545966228893, 'epoch': 4.66} +{'loss': 2.4536, 'learning_rate': 0.00010672607879924954, 'epoch': 4.66} +{'loss': 2.7155, 'learning_rate': 0.00010671669793621013, 'epoch': 4.66} +{'loss': 2.5496, 'learning_rate': 0.00010670731707317075, 'epoch': 4.66} +{'loss': 2.5495, 'learning_rate': 0.00010669793621013134, 'epoch': 4.67} +{'loss': 2.4548, 'learning_rate': 0.00010668855534709194, 'epoch': 4.67} +{'loss': 2.3879, 'learning_rate': 0.00010667917448405253, 'epoch': 4.67} +{'loss': 2.6529, 'learning_rate': 0.00010666979362101315, 'epoch': 4.67} +{'loss': 2.6875, 'learning_rate': 0.00010666041275797374, 'epoch': 4.67} +{'loss': 2.5643, 'learning_rate': 0.00010665103189493435, 'epoch': 4.67} +{'loss': 2.3517, 'learning_rate 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-10000 +[INFO|configuration_utils.py:425] 2021-12-16 18:50:16,269 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-10000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 18:50:19,074 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-10000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 18:50:19,075 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-10000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 18:50:19,075 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-10000/special_tokens_map.json + 47% 10001/21320 [2:30:23<69:30:12, 22.11s/it] 47% 10001/21320 [2:30:23<69:30:12, 22.11s/it] 47% 10002/21320 [2:30:24<49:24:17, 15.71s/it] 47% 10002/21320 [2:30:24<49:24:17, 15.71s/it] 47% 10003/21320 [2:30:25<35:20:21, 11.24s/it] 47% 10003/21320 [2:30:25<35:20:21, 11.24s/it] 47% 10004/21320 [2:30:26<25:36:12, 8.15s/it] 47% 10004/21320 [2:30:26<25:36:12, 8.15s/it] 47% 10005/21320 [2:30:26<18:40:37, 5.94s/it] 47% 10005/21320 [2:30:26<18:40:37, 5.94s/it] 47% 10006/21320 [2:30:27<13:51:43, 4.41s/it] 47% 10006/21320 [2:30:27<13:51:43, 4.41s/it] 47% 10007/21320 [2:30:28<10:30:00, 3.34s/it] 47% 10007/21320 [2:30:28<10:30:00, 3.34s/it] 47% 10008/21320 [2:30:29<8:08:44, 2.59s/it] 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9.881801125703564e-05, 'epoch': 5.06} +{'loss': 2.198, 'learni 51% 10788/21320 [2:41:19<2:23:40, 1.22it/s]ng_rate': 9.880863039399625e-05, 'epoch': 5.06} + 51% 10789/21320 [2:41:20<2:27:53, 1.19it/s] 51% 10789/21320 [2:41:20<2:27:53, 1.19it/s] 51% 10790/21320 [2:41:21<2:28:28, 1.18it/s] 51% 10790/21320 [2:41:21<2:28:28, 1.18it/s] 51% 10791/21320 [2:41:22<2:29:07, 1.18it/s] 51% 10791/21320 [2:41:22<2:29:07, 1.18it/s] 51% 10792/21320 [2:41:22<2:28:52, 1.18it/s] 51% 10792/21320 [2:41:22<2:28:52, 1.18it/s] 51% 10793/21320 [2:41:23<2:27:46, 1.19it/s] 51% 10793/21320 [2:41:23<2:27:46, 1.19it/s] 51% 10794/21320 [2:41:24<2:29:20, 1.17it/s] 51% 10794/21320 [2:41:24<2:29:20, 1.17it/s] 51% 10795/21320 [2:41:25<2:25:42, 1.20it/s] 51% 10795/21320 [2:41:25<2:25:42, 1.20it/s] 51% 10796/21320 [2:41:26<2:24:45, 1.21it/s] 51% 10796/21320 [2:41:26<2:24:45, 1.21it/s] 51% 10797/21320 [2:41:27<2:23:55, 1.22it/s] 51% 10797/21320 [2:41:27<2:23:55, 1.22it/s] 51% 10798/21320 [2:41:27<2:25:31, 1.21it/s] 51% 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[2:44:13<2:22:14, 1.21it/s] 52% 10999/21320 [2:44:14<2:21:15, 1.22it/s] 52% 10999/21320 [2:44:14<2:21:15, 1.22it/s] 52% 11000/21320 [2:44:15<2:22:20, 1.21it/s] 52% 11000/21320 [2:44:15<2:22:20, 1.21it/s][INFO|trainer.py:2281] 2021-12-16 19:04:12,082 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 19:04:12,082 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 19:04:12,082 >> Batch size = 8 + +{'loss': 2.7168, 'learning_rate': 9.77298311444653e-05, 'epoch': 5.11} +{'loss': 2.3631, 'learning_rate': 9.77204502814259e-05, 'epoch': 5.11} +{'loss': 2.3664, 'learning_rate': 9.771106941838649e-05, 'epoch': 5.11} +{'loss': 2.508, 'learning_rate': 9.770168855534709e-05, 'epoch': 5.11} +{'loss': 2.4268, 'learning_rate': 9.76923076923077e-05, 'epoch': 5.12} +{'loss': 2.321, 'learning_rate': 9.76829268292683e-05, 'epoch': 5.12} +{'loss': 2.2304, 'learning_rate': 9.76735459662289e-05, 'epoch': 5.12} +{'loss': 2.6101, 'learning_rate': 9.76641651031895e-05, 'epoch': 5.12} 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Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-12000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 19:20:23,548 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-12000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 19:20:23,549 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-12000/special_tokens_map.json + 56% 12001/21320 [3:00:27<57:25:39, 22.18s/it] 56% 12001/21320 [3:00:27<57:25:39, 22.18s/it] 56% 12002/21320 [3:00:28<40:48:54, 15.77s/it] 56% 12002/21320 [3:00:28<40:48:54, 15.77s/it] 56% 12003/21320 [3:00:29<29:13:01, 11.29s/it] 56% 12003/21320 [3:00:29<29:13:01, 11.29s/it] 56% 12004/21320 [3:00:30<21:04:16, 8.14s/it] 56% 12004/21320 [3:00:30<21:04:16, 8.14s/it] 56% 12005/21320 [3:00:31<15:23:47, 5.95s/it] 56% 12005/21320 [3:00:31<15:23:47, 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1.19it/s] 61% 12996/21320 [3:14:17<1:54:50, 1.21it/s] 61% 12996/21320 [3:14:17<1:54:50, 1.21it/s] 61% 12997/21320 [3:14:17<1:54:00, 1.22it/s] 61% 12997/21320 [3:14:17<1:54:00, 1.22it/s] 61% 12998/21320 [3:14:18<1:52:50, 1.23it/s] 61% 12998/21320 [3:14:18<1:52:50, 1.23it/s] 61% 12999/21320 [3:14:19<1:52:26, 1.23it/s] 61% 12999/21320 [3:14:19<1:52:26, 1.23it/s] 61% 13000/21320 [3:14:20<1:56:36, 1.19it/s] 61% 13000/21320 [3:14:20<1:56:36, 1.19it/s][INFO|trainer.py:2281] 2021-12-16 19:34:17,132 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 19:34:17,132 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 19:34:17,132 >> Batch size = 8 + + 0% 0/237 [00:00> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 19:49:19,409 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 19:49:19,409 >> Batch size = 8 +{'loss': 2.3493, 'learning_rate': 6.951219512195122e-05, 'epoch': 6.52} +{'loss': 2.3537, 'learning_rate': 6.950281425891182e-05, 'epoch': 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'epoch': 6.56} +{'loss': 2.3843, 'learning_rate': 6.872420262664165e-05, 'epoch': 6.56} +{'loss': 2.4019, 'learning_rate': 6.871482176360225e-05, 'epoch': 6.56} +{'loss': 2.3952, 'learning_rate': 6.870544090056286e-05, 'epoch': 6.56} +{'loss': 2.194, 'learning_rate': 6.869606003752346e-05, 'epoch': 6.57} +{'loss': 2.2025, 'learning_rate': 6.868667917448405e-05, 'epoch': 6.57} +{'loss': 2.4951, 'learning_rate': 6.867729831144466e-05, 'epoch': 6.57} +{'loss': 1.9833, 'learning_rate': 6.866791744840526e-05, 'epoch': 6.57} + 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-14000 +[INFO|configuration_utils.py:425] 2021-12-16 19:50:27,172 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-14000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 19:50:29,987 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-14000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 19:50:29,988 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-14000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 19:50:29,988 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-14000/special_tokens_map.json + 66% 14001/21320 [3:30:34<45:01:27, 22.15s/it] 66% 14001/21320 [3:30:34<45:01:27, 22.15s/it] 66% 14002/21320 [3:30:35<32:02:15, 15.76s/it] 66% 14002/21320 [3:30:35<32:02:15, 15.76s/it] 66% 14003/21320 [3:30:36<22:58:59, 11.31s/it] 66% 14003/21320 [3:30:36<22:58:59, 11.31s/it] 66% 14004/21320 [3:30:37<16:35:48, 8.17s/it] 66% 14004/21320 [3:30:37<16:35:48, 8.17s/it] 66% 14005/21320 [3:30:37<12:07:37, 5.97s/it] 66% 14005/21320 [3:30:37<12:07:37, 5.97s/it] 66% 14006/21320 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[3:44:24<1:29:37, 1.18it/s] 70% 14996/21320 [3:44:24<1:29:37, 1.18it/s] 70% 14997/21320 [3:44:24<1:28:26, 1.19it/s] 70% 14997/21320 [3:44:24<1:28:26, 1.19it/s] 70% 14998/21320 [3:44:25<1:28:06, 1.20it/s] 70% 14998/21320 [3:44:25<1:28:06, 1.20it/s] 70% 14999/21320 [3:44:26<1:26:59, 1.21it/s] 70% 14999/21320 [3:44:26<1:26:59, 1.21it/s] 70% 15000/21320 [3:44:27<1:28:35, 1.19it/s] 70% 15000/21320 [3:44:27<1:28:35, 1.19it/s][INFO|trainer.py:2281] 2021-12-16 20:04:24,142 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 20:04:24,142 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 20:04:24,142 >> Batch size = 8 +{'loss': 2.4355, 'learning_rate': 6.013133208255159e-05, 'epoch': 6.99} +{'loss': 2.4428, 'learning_rate': 6.01219512195122e-05, 'epoch': 6.99} +{'loss': 2.3906, 'learning_rate': 6.0112570356472795e-05, 'epoch': 6.99} +{'loss': 2.2098, 'learning_rate': 6.01031894934334e-05, 'epoch': 6.99} +{'loss': 2.5512, 'learning_rate': 6.0093808630394e-05, 'epoch': 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'epoch': 8.44} +{'loss': 2.1439, 'learning_rate': 3.122889305816135e-05, 'epoch': 8.44} +{'loss': 2.3091, 'learning_rate': 3.1219512195121955e-05, 'epoch': 8.44} +{'loss': 2.3091, 'learning_rate': 3.121013133208255e-05, 'epoch': 8.44} +{'loss': 2.0815, 'learning_rate': 3.120075046904316e-05, 'epoch': 8.44} +{'loss': 2.2012, 'learning_rate': 3.1191369606003755e-05, 'epoch': 8.44} +{'loss': 2.4012, 'learning_rate': 3.118198874296435e-05, 'epoch': 8.44} +{'loss': 2.2108, 'learning_rate': 3.117260787992495e-05, 'epoch': 8.44} +{'loss': 2.1813, 'learning_rate': 3.1163227016885555e-05, 'epoch': 8.44} +{'loss': 2.3401, 'learning_rate': 3.115384615384615e-05, 'epoch': 8.44} +{'loss': 2.4014, 'learning_rate': 3.114446529080676e-05, 'epoch': 8.44} + 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-18000 +[INFO|configuration_utils.py:425] 2021-12-16 20:50:44,241 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-18000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 20:50:47,046 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-18000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 20:50:47,048 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-18000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 20:50:47,048 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-18000/special_tokens_map.json + 84% 18001/21320 [4:30:51<20:27:35, 22.19s/it] 84% 18001/21320 [4:30:51<20:27:35, 22.19s/it] 84% 18002/21320 [4:30:52<14:32:13, 15.77s/it] 84% 18002/21320 [4:30:52<14:32:13, 15.77s/it] 84% 18003/21320 [4:30:53<10:23:40, 11.28s/it] 84% 18003/21320 [4:30:53<10:23:40, 11.28s/it] 84% 18004/21320 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[4:42:58<32:50, 1.24it/s] 89% 18875/21320 [4:42:58<33:17, 1.22it/s] 89% 18875/21320 [4:42:58<33:17, 1.22it/s] 89% 18876/21320 [4:42:59<35:21, 1.15it/s] 89% 18876/21320 [4:42:59<35:21, 1.15it/s] 89% 18877/21320 [4:43:00<35:11, 1.16it/s] 89% 18877/21320 [4:43:00<35:11, 1.16it/s] 89% 18878/21320 [4:43:01<34:51, 1.17it/s] 89% 18878/21320 [4:43:01<34:51, 1.17it/s] 89% 18879/21320 [4:43:02<34:47, 1.17it/s] 89% 18879/21320 [4:43:02<34:47, 1.17it/s] 89% 18880/21320 [4:43:03<34:46, 1.17it/s] 89% 18880/21320 [4:43:03<34:46, 1.17it/s] 89% 18881/21320 [4:43:04<34:45, 1.17it/s] 89% 18881/21320 [4:43:04<34:45, 1.17it/s] 89% 18882/21320 [4:43:05<34:06, 1.19it/s] 89% 18882/21320 [4:43:05<34:06, 1.19it/s] 89% 18883/21320 [4:43:05<33:41, 1.21it/s] 89% 18883/21320 [4:43:05<33:41, 1.21it/s] 89% 18884/21320 [4:43:06<33:24, 1.22it/s] 89% 18884/21320 [4:43:06<33:24, 1.22it/s] 89% 18885/21320 [4:43:07<33:04, 1.23it/s] 89% 18885/21320 [4:43:07<33:04, 1.23it/s] 89% 18886/21320 [4:43:08<34:22, 1.18it/s] 89% 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21:04:40,496 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 21:04:40,497 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 21:04:40,497 >> Batch size = 8 + + 0% 0/237 [00:00> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 21:19:40,675 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 21:19:40,675 >> Batch size = 8 +{'loss': 2.3654, 'learning_rate': 1.3330206378986867e-05, 'epoch': 9.33} +{'loss': 2.1927, 'learning_rate': 1.3320825515947468e-05, 'epoch': 9.33} +{'loss': 2.252, 'learning_rate': 1.3311444652908068e-05, 'epoch': 9.33} +{'loss': 2.5268, 'learning_rate': 1.3302063789868669e-05, 'epoch': 9.33} +{'loss': 2.2322, 'learning_rate': 1.329268292682927e-05, 'epoch': 9.34} +{'loss': 2.0964, 'learning_rate': 1.3283302063789867e-05, 'epoch': 9.34} +{'loss': 2.2146, 'learning_rate': 1.3273921200750469e-05, 'epoch': 9.34} +{'loss': 2.1842, 'learning_rate': 1.3264540337711071e-05, 'epoch': 9.34} +{'loss': 2.3994, 'learning_rate': 1.3255159474671672e-05, 'epoch': 9.34} +{'loss': 2.2511, 'learning_rate': 1.324577861163227e-05, 'epoch': 9.34} +{'loss': 2.2697, 'learning_rate': 1.3236397748592871e-05, 'epoch': 9.34} +{'loss': 2.2788, 'learning_rate': 1.3227016885553472e-05, 'epoch': 9.34} +{'loss': 2.4691, 'learning_rate': 1.3217636022514072e-05, 'epoch': 9.34} +{'loss': 2.3393, 'learning_rate': 1.3208255159474673e-05, 'epoch': 9.34} +{'loss': 2.3339, 'learning_rate': 1.3198874296435274e-05, 'epoch': 9.34} +{'loss': 2.0519, 'learning_rate': 1.3189493433395872e-05, 'epoch': 9.34} +{'loss': 2.1329, 'learning_rate': 1.3180112570356473e-05, 'epoch': 9.34} +{'loss': 2.2017, 'learning_rate': 1.3170731707317074e-05, 'epoch': 9.34} +{'loss': 2.2765, 'learning_rate': 1.3161350844277673e-05, 'epoch': 9.34} +{'loss': 2.3263, 'learning_rate': 1.3151969981238274e-05, 'epoch': 9.34} +{'loss': 2.2922, 'learning_rate': 1.3142589118198876e-05, 'epoch': 9.34} +{'loss': 2.2653, 'learning_rate': 1.3133208255159477e-05, 'epoch': 9.34} +{'loss': 2.2427, 'learning_rate': 1.3123827392120074e-05, 'epoch': 9.34} +{'loss': 2.3225, 'learning_rate': 1.3114446529080676e-05, 'epoch': 9.34} +{'loss': 2.3877, 'learning_rate': 1.3105065666041277e-05, 'epoch': 9.34} +{'loss': 2.3842, 'learning_rate': 1.3095684803001876e-05, 'epoch': 9.35} +{'loss': 2.0923, 'learning_rate': 1.3086303939962477e-05, 'epoch': 9.35} +{'loss': 2.181, 'learning_rate': 1.3076923076923078e-05, 'epoch': 9.35} +{'loss': 2.5466, 'learning_rate': 1.3067542213883676e-05, 'epoch': 9.35} +{'loss': 2.2384, 'learning_rate': 1.3058161350844279e-05, 'epoch': 9.35} +{'loss': 2.2247, 'learning_rate': 1.304878048780488e-05, 'epoch': 9.35} +{'loss': 2.3402, 'learning_rate': 1.3039399624765481e-05, 'epoch': 9.35} +{'loss': 2.3933, 'learning_rate': 1.3030018761726079e-05, 'epoch': 9.35} +{'loss': 2.0918, 'learning_rate': 1.302063789868668e-05, 'epoch': 9.35} +{'loss': 2.182, 'learning_rate': 1.3011257035647281e-05, 'epoch': 9.35} +{'loss': 2.2968, 'learning_rate': 1.300187617260788e-05, 'epoch': 9.35} +{'loss': 2.0703, 'learning_rate': 1.2992495309568481e-05, 'epoch': 9.35} +{'loss': 2.1339, 'learning_rate': 1.2983114446529083e-05, 'epoch': 9.35} +{'loss': 2.4522, 'learning_rate': 1.297373358348968e-05, 'epoch': 9.35} +{'loss': 2.1297, 'learning_rate': 1.2964352720450281e-05, 'epoch': 9.35} +{'loss': 2.1957, 'learning_rate': 1.2954971857410882e-05, 'epoch': 9.35} +{'loss': 2.5211, 'learning_rate': 1.2945590994371482e-05, 'epoch': 9.35} +{'loss': 2.1509, 'learning_rate': 1.2936210131332083e-05, 'epoch': 9.35} +{'loss': 2.1635, 'learning_rate': 1.2926829268292684e-05, 'epoch': 9.35} +{'loss': 2.1668, 'learning_rate': 1.2917448405253285e-05, 'epoch': 9.35} +{'loss': 2.1776, 'learning_rate': 1.2908067542213883e-05, 'epoch': 9.35} +{'loss': 2.037, 'learning_rate': 1.2898686679174484e-05, 'epoch': 9.36} +{'loss': 2.2911, 'learning_rate': 1.2889305816135087e-05, 'epoch': 9.36} +{'loss': 2.416, 'learning_rate': 1.2879924953095685e-05, 'epoch': 9.36} +{'loss': 2.3219, 'learning_rate': 1.2870544090056286e-05, 'epoch': 9.36} +{'loss': 2.2113, 'learning_rate': 1.2861163227016887e-05, 'epoch': 9.36} +{'loss': 2.2032, 'learning_rate': 1.2851782363977486e-05, 'epoch': 9.36} +{'loss': 2.1858, 'learning_rate': 1.2842401500938087e-05, 'epoch': 9.36} +{'loss': 2.1528, 'learning_rate': 1.2833020637898688e-05, 'epoch': 9.36} +{'loss': 2.2252, 'learning_rate': 1.282363977485929e-05, 'epoch': 9.36} +{'loss': 2.5649, 'learning_rate': 1.2 + 0% 0/237 [00:00> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-20000 +[INFO|configuration_utils.py:425] 2021-12-16 21:20:48,515 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-20000/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 21:20:51,386 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-20000/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 21:20:51,387 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-20000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 21:20:51,387 >> Special tokens file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/checkpoint-20000/special_tokens_map.json + 94% 20001/21320 [5:00:56<8:08:06, 22.20s/it] 94% 20001/21320 [5:00:56<8:08:06, 22.20s/it] 94% 20002/21320 [5:00:56<5:46:39, 15.78s/it] 94% 20002/21320 [5:00:56<5:46:39, 15.78s/it] 94% 20003/21320 [5:00:57<4:07:46, 11.29s/it] 94% 20003/21320 [5:00:57<4:07:46, 11.29s/it] 94% 20004/21320 [5:00:58<2:58:25, 8.14s/it] 94% 20004/21320 [5:00:58<2:58:25, 8.14s/it] 94% 20005/21320 [5:00:59<2:10:06, 5.94s/it] 94% 20005/21320 [5:00:59<2:10:06, 5.94s/it] 94% 20006/21320 [5:01:00<1:36:17, 4.40s/it] 94% 20006/21320 [5:01:00<1:36:17, 4.40s/it] 94% 20007/21320 [5:01:00<1:12:37, 3.32s/it] 94% 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[5:07:10<12:29, 1.16it/s] 96% 20454/21320 [5:07:11<12:23, 1.16it/s] 96% 20454/21320 [5:07:11<12:23, 1.16it/s] 96% 20455/21320 [5:07:12<12:23, 1.16it/s] 96% 20455/21320 [5:07:12<12:23, 1.16it/s] 96% 20456/21320 [5:07:13<12:41, 1.13it/s] 96% 20456/21320 [5:07:13<12:41, 1.13it/s] 96% 20457/21320 [5:07:14<12:25, 1.16it/s] 96% 20457/21320 [5:07:14<12:25, 1.16it/s] 96% 20458/21320 [5:07:15<12:09, 1.18it/s] 96% 20458/21320 [5:07:15<12:09, 1.18it/s] 96% 20459/21320 [5:07:15<12:00, 1.19it/s] 96% 20459/21320 [5:07:15<12:00, 1.19it/s] 96% 20460/21320 [5:07:16<11:57, 1.20it/s] 96% 20460/21320 [5:07:16<11:57, 1.20it/s] 96% 20461/21320 [5:07:17<12:04, 1.19it/s] 96% 20461/21320 [5:07:17<12:04, 1.19it/s] 96% 20462/21320 [5:07:18<11:59, 1.19it/s] 96% 20462/21320 [5:07:18<11:59, 1.19it/s] 96% 20463/21320 [5:07:19<11:58, 1.19it/s] 96% 20463/21320 [5:07:19<11:58, 1.19it/s] 96% 20464/21320 [5:07:19<11:49, 1.21it/s] 96% 20464/21320 [5:07:19<11:49, 1.21it/s] 96% 20465/21320 [5:07:20<11:43, 1.22it/s] 96% 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20994/21320 [5:14:40<04:24, 1.23it/s] 98% 20995/21320 [5:14:41<04:22, 1.24it/s] 98% 20995/21320 [5:14:41<04:22, 1.24it/s] 98% 20996/21320 [5:14:42<04:20, 1.25it/s] 98% 20996/21320 [5:14:42<04:20, 1.25it/s] 98% 20997/21320 [5:14:43<04:19, 1.24it/s] 98% 20997/21320 [5:14:43<04:19, 1.24it/s] 98% 20998/21320 [5:14:43<04:19, 1.24it/s] 98% 20998/21320 [5:14:43<04:19, 1.24it/s] 98% 20999/21320 [5:14:44<04:19, 1.24it/s] 98% 20999/21320 [5:14:44<04:19, 1.24it/s] 98% 21000/21320 [5:14:45<04:17, 1.24it/s] 98% 21000/21320 [5:14:45<04:17, 1.24it/s][INFO|trainer.py:2281] 2021-12-16 21:34:42,192 >> ***** Running Evaluation ***** +[INFO|trainer.py:2283] 2021-12-16 21:34:42,192 >> Num examples = 1895 +[INFO|trainer.py:2286] 2021-12-16 21:34:42,192 >> Batch size = 8 +{'loss': 2.3339, 'learning_rate': 3.874296435272045e-06, 'epoch': 9.81} +{'loss': 2.3267, 'learning_rate': 3.8649155722326454e-06, 'epoch': 9.81} +{'loss': 2.2406, 'learning_rate': 3.855534709193246e-06, 'epoch': 9.81} +{'loss': 2.3742, 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Do not forget to share your model on huggingface.co/models =) + + + 100% 21320/21320 [5:20:21<00:00, 1.22it/s] 100% 21320/21320 [5:20:21<00:00, 1.11it/s] +[INFO|trainer.py:2033] 2021-12-16 21:40:17,744 >> Saving model checkpoint to /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1 +[INFO|configuration_utils.py:425] 2021-12-16 21:40:17,745 >> Configuration saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/config.json +[INFO|modeling_utils.py:1070] 2021-12-16 21:40:20,666 >> Model weights saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/pytorch_model.bin +[INFO|tokenization_utils_base.py:2043] 2021-12-16 21:40:20,667 >> tokenizer config file saved in /data1/vchua/runs-pegasus-hf4p13/pegasus-ft/pegasus-billsum-10eph-run1/tokenizer_config.json +[INFO|tokenization_utils_base.py:2049] 2021-12-16 21:40:20,667 >> Special tokens file saved in 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'billsum', 'args': 'default'}} +***** eval metrics ***** + epoch = 10.0 + eval_loss = 2.6152 + eval_runtime = 0:01:08.11 + eval_samples = 1895 + eval_samples_per_second = 27.823 + eval_steps_per_second = 3.48 +wandb: Waiting for W&B process to finish, PID 49042... (success). +wandb: - 0.00MB of 0.00MB uploaded (0.00MB deduped) wandb: \ 0.00MB of 0.00MB uploaded (0.00MB deduped) wandb: | 0.00MB of 0.00MB uploaded (0.00MB deduped) wandb: / 0.00MB of 1.55MB uploaded (0.00MB deduped) wandb: - 0.00MB of 1.55MB uploaded (0.00MB deduped) wandb: \ 0.00MB of 1.55MB uploaded (0.00MB deduped) wandb: | 1.36MB of 1.55MB uploaded (0.00MB deduped) wandb: / 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: - 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: \ 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: | 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: / 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: - 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: \ 1.55MB of 1.55MB uploaded (0.00MB deduped) wandb: +wandb: Run history: +wandb: eval/loss █▅▄▃▂▂▁▁▁▁▁▁▁▁▁▁▁▂▁▂▂▂ +wandb: eval/runtime ▁▃▁▆▄▅▅▅▆▆▆▇▆▆▆▅▆▆▅▆██ +wandb: eval/samples_per_second █▆█▃▅▄▄▄▃▃▃▂▃▃▃▄▃▂▄▃▁▁ +wandb: eval/steps_per_second █▆█▄▅▄▄▄▃▃▃▂▃▃▃▄▃▂▄▃▁▁ +wandb: train/epoch ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ +wandb: train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ +wandb: train/learning_rate ███▇▇▇▇▇▇▆▆▆▆▆▆▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▂▂▂▂▂▂▁▁▁ +wandb: train/loss ██▇▆▅▅▅▄▃▆▅▃▁▄▄▅▅▃▁▄▂▁▄▂▃▂▂▂▃▄▄▂▂▂▃▂▂▁▂▃ +wandb: train/total_flos ▁ +wandb: train/train_loss ▁ +wandb: train/train_runtime ▁ +wandb: train/train_samples_per_second ▁ +wandb: train/train_steps_per_second ▁ +wandb: +wandb: Run summary: +wandb: eval/loss 2.61525 +wandb: eval/runtime 68.1101 +wandb: eval/samples_per_second 27.823 +wandb: eval/steps_per_second 3.48 +wandb: train/epoch 10.0 +wandb: train/global_step 21320 +wandb: train/learning_rate 0.0 +wandb: train/loss 2.329 +wandb: train/total_flos 6.151649647041577e+17 +wandb: train/train_loss 2.48211 +wandb: train/train_runtime 19223.3768 +wandb: train/train_samples_per_second 8.871 +wandb: train/train_steps_per_second 1.109 +wandb: +wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s) +wandb: Synced pegasus-billsum-10eph-run1: https://wandb.ai/vchua/csr-dgx1-04_pegasus_ft/runs/3c10akuv +wandb: Find logs at: ./wandb/run-20211216_161954-3c10akuv/logs/debug.log +wandb: +