jialicheng
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Commit
•
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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +55 -0
- added_tokens.json +3 -0
- all_results.json +14 -0
- config.json +45 -0
- eval_results.json +8 -0
- pred_logit_eval.npy +3 -0
- pred_logit_test.npy +3 -0
- pred_logit_train.npy +3 -0
- pytorch_model.bin +3 -0
- runs/Apr17_12-36-31_clu/events.out.tfevents.1713357481.clu +3 -0
- runs/Apr21_17-15-24_clu/events.out.tfevents.1713719787.clu +3 -0
- runs/Mar18_14-37-33_clu/1710772688.37095/events.out.tfevents.1710772688.clu +3 -0
- runs/Mar18_14-37-33_clu/events.out.tfevents.1710772688.clu +3 -0
- runs/Mar18_14-37-33_clu/events.out.tfevents.1710773859.clu +3 -0
- special_tokens_map.json +9 -0
- spm.model +3 -0
- test_results.json +8 -0
- tokenizer.json +0 -0
- tokenizer_config.json +16 -0
- train_results.json +8 -0
- trainer_state.json +157 -0
- training_args.bin +3 -0
README.md
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---
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license: mit
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base_model: microsoft/deberta-v3-base
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tags:
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- generated_from_trainer
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model-index:
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- name: imdb_42
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# imdb_42
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.0095
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- eval_accuracy: 0.9987
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- eval_runtime: 48.9862
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- eval_samples_per_second: 510.348
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- eval_steps_per_second: 2.001
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- step: 0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 256
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.2+cu118
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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added_tokens.json
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{
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"[MASK]": 128000
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}
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all_results.json
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{
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"epoch": 10.0,
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"eval_accuracy": 0.99872,
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"eval_loss": 0.009523958899080753,
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+
"eval_runtime": 48.9862,
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"eval_samples": 25000,
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"eval_samples_per_second": 510.348,
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"eval_steps_per_second": 2.001,
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"train_loss": 0.07955141689466394,
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"train_runtime": 1147.935,
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"train_samples": 25000,
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"train_samples_per_second": 217.782,
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"train_steps_per_second": 6.812
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}
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config.json
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{
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"_name_or_path": "microsoft/deberta-v3-base",
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"architectures": [
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"DebertaV2ForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"finetuning_task": "text-classification",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "0",
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"1": "1"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"0": 0,
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"1": 1
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},
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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"max_relative_positions": -1,
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"model_type": "deberta-v2",
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"norm_rel_ebd": "layer_norm",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_dropout": 0,
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"pooler_hidden_act": "gelu",
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"pooler_hidden_size": 768,
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"pos_att_type": [
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"p2c",
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"c2p"
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],
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"position_biased_input": false,
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"position_buckets": 256,
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"problem_type": "single_label_classification",
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"relative_attention": true,
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"share_att_key": true,
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"torch_dtype": "float32",
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"transformers_version": "4.28.0",
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"type_vocab_size": 0,
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"vocab_size": 128100
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}
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eval_results.json
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{
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"eval_accuracy": 0.9136,
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"eval_runtime": 52.5651,
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"eval_samples": 25000,
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"eval_samples_per_second": 475.601,
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"eval_steps_per_second": 1.864
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}
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pred_logit_eval.npy
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pred_logit_test.npy
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pred_logit_train.npy
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pytorch_model.bin
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runs/Apr17_12-36-31_clu/events.out.tfevents.1713357481.clu
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runs/Apr21_17-15-24_clu/events.out.tfevents.1713719787.clu
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runs/Mar18_14-37-33_clu/1710772688.37095/events.out.tfevents.1710772688.clu
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runs/Mar18_14-37-33_clu/events.out.tfevents.1710772688.clu
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runs/Mar18_14-37-33_clu/events.out.tfevents.1710773859.clu
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special_tokens_map.json
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{
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"eos_token": "[SEP]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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spm.model
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version https://git-lfs.github.com/spec/v1
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test_results.json
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{
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"eval_accuracy": 0.9136,
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"eval_loss": 0.5574674010276794,
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"eval_runtime": 49.0027,
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"eval_samples": 25000,
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"eval_samples_per_second": 510.175,
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"eval_steps_per_second": 2.0
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}
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{
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"bos_token": "[CLS]",
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"eos_token": "[SEP]",
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"mask_token": "[MASK]",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"sp_model_kwargs": {},
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"split_by_punct": false,
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"tokenizer_class": "DebertaV2Tokenizer",
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"unk_token": "[UNK]",
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"vocab_type": "spm"
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}
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train_results.json
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{
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"eval_accuracy": 0.99872,
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"eval_loss": 0.009523958899080753,
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"eval_runtime": 48.9862,
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"eval_samples": 25000,
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"eval_samples_per_second": 510.348,
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"eval_steps_per_second": 2.001
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}
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trainer_state.json
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{
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"best_metric": 0.9136,
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{
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"step": 782
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},
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{
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"epoch": 1.28,
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"learning_rate": 4.360613810741688e-05,
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"loss": 0.2741,
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"step": 1000
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},
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{
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"epoch": 2.0,
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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