Ivan Anisimov
commited on
Commit
•
4be731e
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Parent(s):
44887a6
Upload 3 files
Browse files- config.json +113 -0
- pytorch_model.bin +3 -0
- training.log +78 -0
config.json
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{
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"_name_or_path": "",
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"activation_dropout": 0.1,
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"activation_function": "gelu",
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"add_bias_logits": false,
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"add_cross_attention": false,
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"add_final_layer_norm": false,
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"architectures": [
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"BartForConditionalGeneration"
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],
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"attention_dropout": 0.1,
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"bad_words_ids": null,
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"bos_token_id": 0,
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"chunk_size_feed_forward": 0,
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"classif_dropout": 0.1,
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"classifier_dropout": 0.0,
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"clip_val": 2.5,
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"cross_attention_hidden_size": null,
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"d_model": 1024,
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"decoder_attention_heads": 16,
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"decoder_ffn_dim": 4096,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 1,
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"decoder_start_token_id": 2,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"dropout": 0.1,
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"early_stopping": true,
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"encoder_attention_heads": 16,
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"encoder_ffn_dim": 4096,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 3,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": 2,
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"finetuning_task": null,
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"forced_bos_token_id": 0,
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"forced_eos_token_id": 2,
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"gradient_checkpointing": false,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"init_std": 0.02,
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"input_bits": 8,
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"is_decoder": false,
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"is_encoder_decoder": true,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"length_penalty": 1.0,
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"max_length": 20,
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"max_position_embeddings": 1024,
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"min_length": 0,
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"model_type": "bart",
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"no_repeat_ngram_size": 3,
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"normalize_before": false,
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"num_beam_groups": 1,
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"num_beams": 4,
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"num_hidden_layers": 12,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_scores": false,
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"pad_token_id": 1,
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"quantize_act": true,
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"remove_invalid_values": false,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"scale_embedding": false,
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"sep_token_id": null,
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"task_specific_params": {
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"summarization": {
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"length_penalty": 1.0,
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"max_length": 128,
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"min_length": 12,
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"num_beams": 4
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},
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"summarization_cnn": {
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"length_penalty": 2.0,
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"max_length": 142,
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"min_length": 56,
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"num_beams": 4
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},
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"summarization_xsum": {
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"length_penalty": 1.0,
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"max_length": 62,
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"min_length": 11,
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"num_beams": 6
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}
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},
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"temperature": 1.0,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": true,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torch_dtype": "float32",
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"torchscript": false,
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"transformers_version": "4.7.0.dev0",
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"typical_p": 1.0,
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"use_bfloat16": false,
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"use_cache": true,
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"vocab_size": 50265,
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"vocab_size_or_config_json_file": -1,
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"weight_bits": 16
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:82d38521aafb43be1c0b9f93be9c8f4011558be849ca4a9414bb949a32b09d0a
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size 432907017
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training.log
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08/13/2023 00:40:06 - INFO - __main__ - Distributed environment: NO
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Num processes: 1
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Process index: 0
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Local process index: 0
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Device: cuda
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Use FP16 precision: False
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08/13/2023 00:40:06 - WARNING - __main__ - Namespace(dataset_name='s-nlp/paradetox', dataset_config_name=None, train_file=None, ignore_pad_token_for_loss=True, max_source_length=1024, source_prefix=None, preprocessing_num_workers=None, overwrite_cache=None, max_target_length=128, val_max_target_length=None, pad_to_max_length=False, model_name_or_path='s-nlp/bart-base-detox', config_name=None, tokenizer_name=None, text_column=None, summary_column=None, use_slow_tokenizer=False, per_device_train_batch_size=8, per_device_eval_batch_size=4, learning_rate=3e-05, weight_decay=0.0, num_train_epochs=10, max_train_steps=None, gradient_accumulation_steps=2, lr_scheduler_type=<SchedulerType.LINEAR: 'linear'>, warmup_ratio=0.05, output_dir='./output_s-nlp/paradetox_bart_base_detox/16_8_3_1_10_3e-05_fp16', seed=28, model_type=None, teacher_model='s-nlp/bart-base-detox', student_model='s-nlp/bart-base-detox', pred_distill=True, intermediate_distill=True, weight_bits=16, input_bits=8, clip_val=2.5, length_penalty=150, max_length=62, min_length=11, num_beams=6, do_train=True, do_test=True, test_teacher=False, distill_encoder=3, distill_decoder=1, log_steps=20, local_rank=0, weighted=False, new_distill_map=False, task_weight=1, logits_weight=1, hid_weight=1)
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08/13/2023 00:40:24 - INFO - __main__ - ***** Running training *****
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08/13/2023 00:40:24 - INFO - __main__ - Num examples = 19546
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08/13/2023 00:40:24 - INFO - __main__ - Num Epochs = 10
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08/13/2023 00:40:24 - INFO - __main__ - Instantaneous batch size per device = 8
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08/13/2023 00:40:24 - INFO - __main__ - Total train batch size (w. parallel, distributed & accumulation) = 16
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08/13/2023 00:40:24 - INFO - __main__ - Gradient Accumulation steps = 2
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08/13/2023 00:40:24 - INFO - __main__ - Total optimization steps = 24440
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08/13/2023 00:40:24 - INFO - __main__ - student encoder layers = 3
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08/13/2023 00:40:24 - INFO - __main__ - student decoder layers = 1
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08/13/2023 00:40:24 - INFO - __main__ - student encoder layers [0, 1, 2] is mapped with teacher encoder layers [0, 2, 5]
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08/13/2023 00:40:24 - INFO - __main__ - student decoder layers [0] is mapped with teacher decoder layers [5]
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08/13/2023 00:48:32 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 22.59420505922646}
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08/13/2023 00:57:03 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 54.978123489133125}
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08/13/2023 01:05:13 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 62.023727727095206}
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08/13/2023 01:13:26 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 63.97172971159594}
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08/13/2023 01:21:23 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 64.5360970481176}
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08/13/2023 01:29:39 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 64.94717856121133}
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08/13/2023 01:37:40 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 64.59791205000518}
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08/13/2023 01:45:57 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 65.09188210629405}
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08/13/2023 01:54:25 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 65.43488256903395}
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08/13/2023 02:02:48 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 65.13437994345524}
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08/13/2023 13:33:25 - WARNING - __main__ - You're running a t5 model but didn't provide a source prefix, which is the expected, e.g. with `--source_prefix 'summarize: ' `
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08/13/2023 13:33:25 - INFO - __main__ - Distributed environment: NO
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Num processes: 1
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Process index: 0
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Local process index: 0
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Device: cuda
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Use FP16 precision: False
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08/13/2023 13:33:25 - WARNING - __main__ - Namespace(dataset_name='s-nlp/paradetox', dataset_config_name=None, train_file=None, ignore_pad_token_for_loss=True, max_source_length=1024, source_prefix=None, preprocessing_num_workers=None, overwrite_cache=None, max_target_length=128, val_max_target_length=None, pad_to_max_length=False, model_name_or_path='t5-large', config_name=None, tokenizer_name=None, text_column=None, summary_column=None, use_slow_tokenizer=False, per_device_train_batch_size=8, per_device_eval_batch_size=4, learning_rate=3e-05, weight_decay=0.0, num_train_epochs=10, max_train_steps=None, gradient_accumulation_steps=2, lr_scheduler_type=<SchedulerType.LINEAR: 'linear'>, warmup_ratio=0.05, output_dir='./output_s-nlp/paradetox_bart_base_detox/16_8_3_1_10_3e-05_fp16', seed=28, model_type=None, teacher_model='t5-large', student_model='t5-large', pred_distill=True, intermediate_distill=True, weight_bits=16, input_bits=8, clip_val=2.5, length_penalty=150, max_length=62, min_length=11, num_beams=6, do_train=True, do_test=True, test_teacher=False, distill_encoder=3, distill_decoder=1, log_steps=20, local_rank=0, weighted=False, new_distill_map=False, task_weight=1, logits_weight=1, hid_weight=1)
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08/13/2023 13:33:49 - INFO - __main__ - ***** Running training *****
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08/13/2023 13:33:49 - INFO - __main__ - Num examples = 19546
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08/13/2023 13:33:49 - INFO - __main__ - Num Epochs = 10
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08/13/2023 13:33:49 - INFO - __main__ - Instantaneous batch size per device = 8
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08/13/2023 13:33:49 - INFO - __main__ - Total train batch size (w. parallel, distributed & accumulation) = 16
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08/13/2023 13:33:49 - INFO - __main__ - Gradient Accumulation steps = 2
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08/13/2023 13:33:49 - INFO - __main__ - Total optimization steps = 24440
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08/13/2023 13:33:49 - INFO - __main__ - student encoder layers = 3
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08/13/2023 13:33:49 - INFO - __main__ - student decoder layers = 1
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08/13/2023 13:33:49 - INFO - __main__ - student encoder layers [0, 1, 2] is mapped with teacher encoder layers [0, 2, 5]
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08/13/2023 13:33:49 - INFO - __main__ - student decoder layers [0] is mapped with teacher decoder layers [5]
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08/13/2023 18:13:36 - INFO - __main__ - Distributed environment: NO
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Num processes: 1
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Process index: 0
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Local process index: 0
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Device: cuda
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Use FP16 precision: False
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08/13/2023 18:13:36 - WARNING - __main__ - Namespace(dataset_name='s-nlp/paradetox', dataset_config_name=None, train_file=None, ignore_pad_token_for_loss=True, max_source_length=1024, source_prefix=None, preprocessing_num_workers=None, overwrite_cache=None, max_target_length=128, val_max_target_length=None, pad_to_max_length=False, model_name_or_path='facebook/bart-large', config_name=None, tokenizer_name=None, text_column=None, summary_column=None, use_slow_tokenizer=False, per_device_train_batch_size=8, per_device_eval_batch_size=4, learning_rate=3e-05, weight_decay=0.0, num_train_epochs=10, max_train_steps=None, gradient_accumulation_steps=2, lr_scheduler_type=<SchedulerType.LINEAR: 'linear'>, warmup_ratio=0.05, output_dir='./output_s-nlp/paradetox_bart_base_detox/16_8_3_1_10_3e-05_fp16', seed=28, model_type=None, teacher_model='facebook/bart-large', student_model='facebook/bart-large', pred_distill=True, intermediate_distill=True, weight_bits=16, input_bits=8, clip_val=2.5, length_penalty=150, max_length=62, min_length=11, num_beams=6, do_train=True, do_test=True, test_teacher=False, distill_encoder=3, distill_decoder=1, log_steps=20, local_rank=0, weighted=False, new_distill_map=False, task_weight=1, logits_weight=1, hid_weight=1)
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08/13/2023 18:13:57 - INFO - __main__ - ***** Running training *****
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08/13/2023 18:13:57 - INFO - __main__ - Num examples = 19546
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08/13/2023 18:13:57 - INFO - __main__ - Num Epochs = 10
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08/13/2023 18:13:57 - INFO - __main__ - Instantaneous batch size per device = 8
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08/13/2023 18:13:57 - INFO - __main__ - Total train batch size (w. parallel, distributed & accumulation) = 16
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08/13/2023 18:13:57 - INFO - __main__ - Gradient Accumulation steps = 2
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08/13/2023 18:13:57 - INFO - __main__ - Total optimization steps = 24440
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08/13/2023 18:13:57 - INFO - __main__ - student encoder layers = 3
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08/13/2023 18:13:57 - INFO - __main__ - student decoder layers = 1
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08/13/2023 18:13:57 - INFO - __main__ - student encoder layers [0, 1, 2] is mapped with teacher encoder layers [0, 2, 5]
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08/13/2023 18:13:57 - INFO - __main__ - student decoder layers [0] is mapped with teacher decoder layers [5]
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08/13/2023 18:23:59 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 13.927599253697903}
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08/13/2023 18:33:46 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 14.54024753825692}
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08/13/2023 18:43:47 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 15.696559967829156}
|
72 |
+
08/13/2023 18:53:59 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 17.028561047497664}
|
73 |
+
08/13/2023 19:04:19 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 18.190088344180207}
|
74 |
+
08/13/2023 19:14:34 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 19.35744020416755}
|
75 |
+
08/13/2023 19:24:59 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 20.69450840196689}
|
76 |
+
08/13/2023 19:35:05 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 21.69196456544141}
|
77 |
+
08/13/2023 19:45:14 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 22.46896551649043}
|
78 |
+
08/13/2023 19:55:18 - INFO - __main__ - evaluation result: {'accuracy': 0.9501243829727173, 'similarity': 0.5612009167671204, 'fluency': 0.8357802033424377, 'joint': 0.4501223564147949, 'chrF': 22.655778155996654}
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