kkuramitsu
commited on
Commit
•
14f0f69
1
Parent(s):
f576455
first version
Browse files- config.json +31 -0
- generation_config.json +7 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +5 -0
- spiece.model +3 -0
- tokenizer_config.json +12 -0
- train_log.txt +287 -0
config.json
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{
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"_name_or_path": "mini2",
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"architectures": [
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"MT5ForConditionalGeneration"
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],
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"d_ff": 1536,
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"d_kv": 64,
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"d_model": 384,
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"decoder_start_token_id": 0,
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"dense_act_fn": "gelu_new",
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"dropout_rate": 0.1,
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"eos_token_id": 1,
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"feed_forward_proj": "gated-gelu",
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"is_gated_act": true,
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"layer_norm_epsilon": 1e-06,
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"model_type": "mt5",
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"num_decoder_layers": 9,
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"num_heads": 9,
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"num_layers": 9,
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"pad_token_id": 0,
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"relative_attention_max_distance": 128,
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"relative_attention_num_buckets": 32,
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.26.1",
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"use_cache": true,
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"vocab_size": 32128
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}
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generation_config.json
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{
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"_from_model_config": true,
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.26.1"
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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 sha256:6a31e76db56aec04c81affe569cfb952c62ce5dea9f9c59c8593fdc08122d556
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size 321795553
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special_tokens_map.json
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{
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"eos_token": "</s>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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spiece.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:108ea5dbb232558d744aff5011d29b92a76751c210ad8560e6a65738c9630bdf
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size 775057
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tokenizer_config.json
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{
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"additional_special_tokens": [],
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"eos_token": "</s>",
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"extra_ids": 0,
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"model_max_length": 1000000000000000019884624838656,
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"name_or_path": "mini2",
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"pad_token": "<pad>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": "/home/acc12952oa/.cache/huggingface/hub/models--kkuramitsu--mt5np_mini12L/snapshots/e66bd8feec1522ea93ed176acb765f0c44f81526/special_tokens_map.json",
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"tokenizer_class": "T5Tokenizer",
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"unk_token": "<unk>"
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}
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train_log.txt
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_09.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_en_msp_09.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=76.57510 PPL=1803619835086933004964966285967360.00000
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val epoch=1 loss=3.55529 PPL=34.99814
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train epoch=1 loss=3.58229 PPL=35.95572
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[trained] 0.0[H] 41.41847747564316[M] 2485.109[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_09.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_ja_msp_09.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=8.62410 PPL=5564.13037
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val epoch=1 loss=3.48060 PPL=32.47906
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train epoch=1 loss=2.05416 PPL=7.80031
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[trained] 0.0[H] 45.51669268210729[M] 2731.002[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_08.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_en_msp_08.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=5.33357 PPL=207.17598
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val epoch=1 loss=2.69441 PPL=14.79680
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train epoch=1 loss=1.59283 PPL=4.91763
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[trained] 0.0[H] 41.46436125040054[M] 2487.862[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_08.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_ja_msp_08.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=5.03823 PPL=154.19640
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val epoch=1 loss=3.20544 PPL=24.66638
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train epoch=1 loss=1.61361 PPL=5.02092
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[trained] 0.0[H] 45.251987334092455[M] 2715.119[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_07.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_en_msp_07.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=4.14368 PPL=63.03437
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val epoch=1 loss=2.43705 PPL=11.43929
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train epoch=1 loss=1.37564 PPL=3.95763
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[trained] 0.0[H] 41.47204469839732[M] 2488.323[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_07.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_ja_msp_07.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=4.28832 PPL=72.84402
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val epoch=1 loss=3.02900 PPL=20.67647
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train epoch=1 loss=1.48900 PPL=4.43266
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[trained] 0.0[H] 45.57923027674357[M] 2734.754[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_06.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_en_msp_06.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=3.70968 PPL=40.84082
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val epoch=1 loss=2.28623 PPL=9.83775
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train epoch=1 loss=1.27682 PPL=3.58522
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[trained] 0.0[H] 41.4678033153216[M] 2488.068[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_06.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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[train] ['/groups/gcc50582/MSP/mc4_ja_msp_06.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=3.83498 PPL=46.29248
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val epoch=1 loss=2.79002 PPL=16.28134
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train epoch=1 loss=1.41784 PPL=4.12821
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[trained] 0.0[H] 45.09872035185496[M] 2705.923[sec]
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_05.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
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+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_05.jsonl']
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[batch_size] 256
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[accumulate_grad_batches] 2
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val epoch=1 loss=3.38932 PPL=29.64582
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val epoch=1 loss=2.20471 PPL=9.06766
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train epoch=1 loss=1.22078 PPL=3.38983
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[trained] 0.0[H] 41.52079544067383[M] 2491.248[sec]
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+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_05.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
74 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_05.jsonl']
|
75 |
+
[batch_size] 256
|
76 |
+
[accumulate_grad_batches] 2
|
77 |
+
val epoch=1 loss=3.77504 PPL=43.59935
|
78 |
+
val epoch=1 loss=2.75377 PPL=15.70175
|
79 |
+
train epoch=1 loss=1.37220 PPL=3.94404
|
80 |
+
[trained] 0.0[H] 45.1388335108757[M] 2708.330[sec]
|
81 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_04.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
82 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_04.jsonl']
|
83 |
+
[batch_size] 256
|
84 |
+
[accumulate_grad_batches] 2
|
85 |
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val epoch=1 loss=3.05649 PPL=21.25283
|
86 |
+
val epoch=1 loss=2.06552 PPL=7.88940
|
87 |
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train epoch=1 loss=1.18322 PPL=3.26485
|
88 |
+
[trained] 0.0[H] 41.343922030925754[M] 2480.635[sec]
|
89 |
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[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_04.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
90 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_04.jsonl']
|
91 |
+
[batch_size] 256
|
92 |
+
[accumulate_grad_batches] 2
|
93 |
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val epoch=1 loss=3.63945 PPL=38.07071
|
94 |
+
val epoch=1 loss=2.74634 PPL=15.58548
|
95 |
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train epoch=1 loss=1.34129 PPL=3.82397
|
96 |
+
[trained] 0.0[H] 44.50069724321365[M] 2670.042[sec]
|
97 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_03.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
98 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_03.jsonl']
|
99 |
+
[batch_size] 256
|
100 |
+
[accumulate_grad_batches] 2
|
101 |
+
val epoch=1 loss=2.99219 PPL=19.92924
|
102 |
+
val epoch=1 loss=2.11169 PPL=8.26216
|
103 |
+
train epoch=1 loss=1.15597 PPL=3.17710
|
104 |
+
[trained] 0.0[H] 41.03153887987137[M] 2461.892[sec]
|
105 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_03.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
106 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_03.jsonl']
|
107 |
+
[batch_size] 256
|
108 |
+
[accumulate_grad_batches] 2
|
109 |
+
val epoch=1 loss=3.69122 PPL=40.09384
|
110 |
+
val epoch=1 loss=2.79154 PPL=16.30605
|
111 |
+
train epoch=1 loss=1.31323 PPL=3.71816
|
112 |
+
[trained] 0.0[H] 45.27243907054265[M] 2716.346[sec]
|
113 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_02.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
114 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_02.jsonl']
|
115 |
+
[batch_size] 256
|
116 |
+
[accumulate_grad_batches] 2
|
117 |
+
val epoch=1 loss=2.89017 PPL=17.99635
|
118 |
+
val epoch=1 loss=2.05285 PPL=7.79006
|
119 |
+
train epoch=1 loss=1.13480 PPL=3.11056
|
120 |
+
[trained] 0.0[H] 41.108288780848184[M] 2466.497[sec]
|
121 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_02.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
122 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_02.jsonl']
|
123 |
+
[batch_size] 256
|
124 |
+
[accumulate_grad_batches] 2
|
125 |
+
val epoch=1 loss=3.43673 PPL=31.08512
|
126 |
+
val epoch=1 loss=2.64907 PPL=14.14095
|
127 |
+
train epoch=1 loss=1.29298 PPL=3.64363
|
128 |
+
[trained] 0.0[H] 44.97415177822113[M] 2698.449[sec]
|
129 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_01.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
130 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_01.jsonl']
|
131 |
+
[batch_size] 256
|
132 |
+
[accumulate_grad_batches] 2
|
133 |
+
val epoch=1 loss=2.77340 PPL=16.01299
|
134 |
+
val epoch=1 loss=1.99160 PPL=7.32726
|
135 |
+
train epoch=1 loss=1.11733 PPL=3.05667
|
136 |
+
[trained] 0.0[H] 41.14810743729274[M] 2468.886[sec]
|
137 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_01.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
138 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_01.jsonl']
|
139 |
+
[batch_size] 256
|
140 |
+
[accumulate_grad_batches] 2
|
141 |
+
val epoch=1 loss=3.39647 PPL=29.85852
|
142 |
+
val epoch=1 loss=2.36330 PPL=10.62593
|
143 |
+
train epoch=1 loss=1.27496 PPL=3.57856
|
144 |
+
[trained] 0.0[H] 44.73817230463028[M] 2684.290[sec]
|
145 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_00.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
146 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_00.jsonl']
|
147 |
+
[batch_size] 256
|
148 |
+
[accumulate_grad_batches] 2
|
149 |
+
val epoch=1 loss=2.74622 PPL=15.58363
|
150 |
+
val epoch=1 loss=2.00091 PPL=7.39578
|
151 |
+
train epoch=1 loss=1.10269 PPL=3.01226
|
152 |
+
[trained] 0.0[H] 41.041836047172545[M] 2462.510[sec]
|
153 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_00.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini1', num_workers=4, output_path='mini1', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini1', top_k=0, warmup_steps=1, weight_decay=0.0)
|
154 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_00.jsonl']
|
155 |
+
[batch_size] 256
|
156 |
+
[accumulate_grad_batches] 2
|
157 |
+
val epoch=1 loss=3.45477 PPL=31.65103
|
158 |
+
val epoch=1 loss=2.73762 PPL=15.45019
|
159 |
+
train epoch=1 loss=1.25830 PPL=3.51942
|
160 |
+
[trained] 0.0[H] 45.509643785158794[M] 2730.579[sec]
|
161 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_09.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
162 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_09.jsonl']
|
163 |
+
[batch_size] 256
|
164 |
+
[accumulate_grad_batches] 2
|
165 |
+
val epoch=1 loss=2.71395 PPL=15.08881
|
166 |
+
val epoch=1 loss=2.00103 PPL=7.39668
|
167 |
+
train epoch=1 loss=1.09001 PPL=2.97429
|
168 |
+
[trained] 0.0[H] 41.28162391185761[M] 2476.897[sec]
|
169 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_09.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
170 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_09.jsonl']
|
171 |
+
[batch_size] 256
|
172 |
+
[accumulate_grad_batches] 2
|
173 |
+
val epoch=1 loss=3.26547 PPL=26.19238
|
174 |
+
val epoch=1 loss=2.69914 PPL=14.86692
|
175 |
+
train epoch=1 loss=1.24174 PPL=3.46165
|
176 |
+
[trained] 0.0[H] 45.42912646929423[M] 2725.748[sec]
|
177 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_08.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
178 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_08.jsonl']
|
179 |
+
[batch_size] 256
|
180 |
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[accumulate_grad_batches] 2
|
181 |
+
val epoch=1 loss=2.68335 PPL=14.63405
|
182 |
+
val epoch=1 loss=2.00004 PPL=7.38934
|
183 |
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train epoch=1 loss=1.07841 PPL=2.94001
|
184 |
+
[trained] 0.0[H] 41.447514899571736[M] 2486.851[sec]
|
185 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_08.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
186 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_08.jsonl']
|
187 |
+
[batch_size] 256
|
188 |
+
[accumulate_grad_batches] 2
|
189 |
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val epoch=1 loss=3.27115 PPL=26.34149
|
190 |
+
val epoch=1 loss=2.72310 PPL=15.22747
|
191 |
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train epoch=1 loss=1.23098 PPL=3.42457
|
192 |
+
[trained] 0.0[H] 45.18751840988795[M] 2711.251[sec]
|
193 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_07.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
194 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_07.jsonl']
|
195 |
+
[batch_size] 256
|
196 |
+
[accumulate_grad_batches] 2
|
197 |
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val epoch=1 loss=2.57214 PPL=13.09387
|
198 |
+
val epoch=1 loss=1.95365 PPL=7.05438
|
199 |
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train epoch=1 loss=1.06908 PPL=2.91269
|
200 |
+
[trained] 0.0[H] 40.959261027971905[M] 2457.556[sec]
|
201 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_07.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
202 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_07.jsonl']
|
203 |
+
[batch_size] 256
|
204 |
+
[accumulate_grad_batches] 2
|
205 |
+
val epoch=1 loss=3.18254 PPL=24.10785
|
206 |
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val epoch=1 loss=2.68020 PPL=14.58803
|
207 |
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train epoch=1 loss=1.22046 PPL=3.38875
|
208 |
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[trained] 0.0[H] 45.264945685863495[M] 2715.897[sec]
|
209 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_06.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
210 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_06.jsonl']
|
211 |
+
[batch_size] 256
|
212 |
+
[accumulate_grad_batches] 2
|
213 |
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val epoch=1 loss=2.57132 PPL=13.08305
|
214 |
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val epoch=1 loss=1.94033 PPL=6.96107
|
215 |
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train epoch=1 loss=1.06083 PPL=2.88875
|
216 |
+
[trained] 0.0[H] 41.00604948997498[M] 2460.363[sec]
|
217 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_06.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
218 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_06.jsonl']
|
219 |
+
[batch_size] 256
|
220 |
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[accumulate_grad_batches] 2
|
221 |
+
val epoch=1 loss=2.99903 PPL=20.06612
|
222 |
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val epoch=1 loss=2.42283 PPL=11.27773
|
223 |
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train epoch=1 loss=1.20782 PPL=3.34619
|
224 |
+
[trained] 0.0[H] 45.244081223011015[M] 2714.645[sec]
|
225 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_05.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
226 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_05.jsonl']
|
227 |
+
[batch_size] 256
|
228 |
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[accumulate_grad_batches] 2
|
229 |
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val epoch=1 loss=2.55513 PPL=12.87301
|
230 |
+
val epoch=1 loss=1.93933 PPL=6.95411
|
231 |
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train epoch=1 loss=1.05271 PPL=2.86539
|
232 |
+
[trained] 0.0[H] 41.11795919736226[M] 2467.078[sec]
|
233 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_05.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
234 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_05.jsonl']
|
235 |
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[batch_size] 256
|
236 |
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[accumulate_grad_batches] 2
|
237 |
+
[failed] ['/groups/gcc50582/MSP/mc4_ja_msp_05.jsonl'] [Errno 28] No space left on device
|
238 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_04.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
239 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_04.jsonl']
|
240 |
+
[batch_size] 256
|
241 |
+
[accumulate_grad_batches] 2
|
242 |
+
[failed] ['/groups/gcc50582/MSP/mc4_en_msp_04.jsonl'] [Errno 28] No space left on device
|
243 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_04.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
244 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_04.jsonl']
|
245 |
+
[batch_size] 256
|
246 |
+
[accumulate_grad_batches] 2
|
247 |
+
[failed] ['/groups/gcc50582/MSP/mc4_ja_msp_04.jsonl'] [Errno 28] No space left on device
|
248 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_03.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
249 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_03.jsonl']
|
250 |
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[batch_size] 256
|
251 |
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[accumulate_grad_batches] 2
|
252 |
+
[failed] ['/groups/gcc50582/MSP/mc4_en_msp_03.jsonl'] [Errno 28] No space left on device
|
253 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_03.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
254 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_03.jsonl']
|
255 |
+
[batch_size] 256
|
256 |
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[accumulate_grad_batches] 2
|
257 |
+
[failed] ['/groups/gcc50582/MSP/mc4_ja_msp_03.jsonl'] [Errno 28] No space left on device
|
258 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_02.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
259 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_02.jsonl']
|
260 |
+
[batch_size] 256
|
261 |
+
[accumulate_grad_batches] 2
|
262 |
+
[failed] ['/groups/gcc50582/MSP/mc4_en_msp_02.jsonl'] [Errno 28] No space left on device
|
263 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_02.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
264 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_02.jsonl']
|
265 |
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[batch_size] 256
|
266 |
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[accumulate_grad_batches] 2
|
267 |
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[failed] ['/groups/gcc50582/MSP/mc4_ja_msp_02.jsonl'] [Errno 28] No space left on device
|
268 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_01.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
269 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_01.jsonl']
|
270 |
+
[batch_size] 256
|
271 |
+
[accumulate_grad_batches] 2
|
272 |
+
[failed] ['/groups/gcc50582/MSP/mc4_en_msp_01.jsonl'] [Errno 28] No space left on device
|
273 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_01.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
274 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_01.jsonl']
|
275 |
+
[batch_size] 256
|
276 |
+
[accumulate_grad_batches] 2
|
277 |
+
[failed] ['/groups/gcc50582/MSP/mc4_ja_msp_01.jsonl'] [Errno 28] No space left on device
|
278 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_en_msp_00.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
279 |
+
[train] ['/groups/gcc50582/MSP/mc4_en_msp_00.jsonl']
|
280 |
+
[batch_size] 256
|
281 |
+
[accumulate_grad_batches] 2
|
282 |
+
[failed] ['/groups/gcc50582/MSP/mc4_en_msp_00.jsonl'] [Errno 28] No space left on device
|
283 |
+
[hparams] Namespace(accelerator=None, adam_epsilon=1e-08, batch_size=256, cache=False, checkpoint_path=None, desc='', devices=1, early_stopping=False, fast_dev_run=False, files=['/groups/gcc50582/MSP/mc4_ja_msp_00.jsonl'], float32_matmul_precision=None, gradient_accumulation_steps=1, learning_rate=0.0003, max_epochs=1, max_grad_norm=1.0, max_hours=None, max_length=128, model_path='mini2', num_workers=4, output_path='mini2', precision='bf16', pretrain=False, score=None, score_file=None, seed=42, solver='adamw', source_max_length=128, step_batch_size=128, target_max_length=128, tokenizer_path='mini2', top_k=0, warmup_steps=1, weight_decay=0.0)
|
284 |
+
[train] ['/groups/gcc50582/MSP/mc4_ja_msp_00.jsonl']
|
285 |
+
[batch_size] 256
|
286 |
+
[accumulate_grad_batches] 2
|
287 |
+
[failed] ['/groups/gcc50582/MSP/mc4_ja_msp_00.jsonl'] [Errno 28] No space left on device
|