Pushing deberta-v3-large-emotion to hub
Browse files- README.md +80 -0
- added_tokens.json +3 -0
- all_results.json +14 -0
- config.json +47 -0
- eval_results.json +8 -0
- pytorch_model.bin +3 -0
- run_test.sh +1 -0
- run_train.sh +1 -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
- trainer_state.json +325 -0
- training_args.bin +3 -0
README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: deberta-v3-large-emotion-lr7e-6-gas1-ls0.1
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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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# deberta-v3-large-emotion-lr7e-6-gas1-ls0.1
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8311
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- Accuracy: 0.8235
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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: 7e-06
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- train_batch_size: 16
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- eval_batch_size: 16
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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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- lr_scheduler_warmup_steps: 50
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- num_epochs: 10.0
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- label_smoothing_factor: 0.1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.2787 | 0.49 | 100 | 1.1127 | 0.4866 |
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| 1.089 | 0.98 | 200 | 0.9668 | 0.7139 |
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| 0.9134 | 1.47 | 300 | 0.8720 | 0.7834 |
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| 0.8618 | 1.96 | 400 | 0.7726 | 0.7941 |
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| 0.686 | 2.45 | 500 | 0.7337 | 0.8209 |
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| 0.6333 | 2.94 | 600 | 0.7350 | 0.8235 |
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| 0.5765 | 3.43 | 700 | 0.7561 | 0.8235 |
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| 0.5502 | 3.92 | 800 | 0.7273 | 0.8476 |
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| 0.5049 | 4.41 | 900 | 0.8137 | 0.8102 |
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| 0.4695 | 4.9 | 1000 | 0.7581 | 0.8289 |
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| 0.4657 | 5.39 | 1100 | 0.8404 | 0.8048 |
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| 0.4549 | 5.88 | 1200 | 0.7800 | 0.8369 |
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| 0.4305 | 6.37 | 1300 | 0.8575 | 0.8235 |
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| 0.4209 | 6.86 | 1400 | 0.8572 | 0.8102 |
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| 0.3983 | 7.35 | 1500 | 0.8392 | 0.8316 |
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| 0.4139 | 7.84 | 1600 | 0.8152 | 0.8209 |
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| 0.393 | 8.33 | 1700 | 0.8261 | 0.8289 |
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| 0.3979 | 8.82 | 1800 | 0.8328 | 0.8235 |
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| 0.3928 | 9.31 | 1900 | 0.8364 | 0.8209 |
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| 0.3848 | 9.8 | 2000 | 0.8322 | 0.8235 |
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### Framework versions
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- Transformers 4.20.0.dev0
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- Pytorch 1.9.0
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- Datasets 2.2.2
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- Tokenizers 0.11.6
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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": 0.8235294222831726,
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"eval_loss": 0.8311316967010498,
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"eval_runtime": 2.1275,
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"eval_samples": 374,
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"eval_samples_per_second": 175.794,
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"eval_steps_per_second": 11.281,
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"train_loss": 0.5818920486113605,
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"train_runtime": 787.9964,
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"train_samples": 3257,
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"train_samples_per_second": 41.333,
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"train_steps_per_second": 2.589
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}
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config.json
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{
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"_name_or_path": "microsoft/deberta-v3-large",
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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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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": 0,
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"1": 1,
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"2": 2,
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"3": 3
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"0": 0,
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"1": 1,
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"2": 2,
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"3": 3
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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": 16,
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"num_hidden_layers": 24,
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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": 1024,
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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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"relative_attention": true,
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"share_att_key": true,
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"torch_dtype": "float32",
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"transformers_version": "4.20.0.dev0",
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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": 0.8475936055183411,
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"eval_loss": 0.5155109763145447,
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"eval_runtime": 3.3452,
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"eval_samples": 374,
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"eval_samples_per_second": 111.803,
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"eval_steps_per_second": 7.174
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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:e182efbb57bc6e4ecda054f4a41e886d02bcafcf1de64adf784d0e47c61f27ab
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size 1740401579
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run_test.sh
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jbsub -queue x86_1h -cores 4+1 -mem 30g -require a100 -o outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/test.log /dccstor/tslm/envs/anaconda3/envs/tslm-gen/bin/python train_clf.py --model_name_or_path outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/best_checkpoint --train_file data/tweet_eval/emotion/train.csv --validation_file data/tweet_eval/emotion/validation.csv --test_file data/tweet_eval/emotion/test.csv --do_eval --do_predict --report_to none --per_device_eval_batch_size 16 --max_seq_length 256 --output_dir outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/best_checkpoint
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run_train.sh
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jbsub -queue x86_6h -cores 4+1 -mem 30g -require a100 -o outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/train.log /dccstor/tslm/envs/anaconda3/envs/tslm-gen/bin/python train_clf.py --model_name_or_path microsoft/deberta-v3-large --train_file data/tweet_eval/emotion/train.csv --validation_file data/tweet_eval/emotion/validation.csv --do_train --do_eval --per_device_train_batch_size 16 --per_device_eval_batch_size 16 --max_seq_length 256 --learning_rate 7e-6 --output_dir outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1 --evaluation_strategy steps --save_strategy no --warmup_steps 50 --num_train_epochs 10 --overwrite_output_dir --logging_steps 100 --gradient_accumulation_steps 1 --label_smoothing_factor 0.1 --report_to clearml --metric_for_best_model accuracy --logging_dir outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/tb \; rm -rf outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/tb \; rm -rf outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/checkpoint-* \; . outputs/train/tweet_eval2/emotion/deberta-v3-large-emotion-lr7e-6-gas1-ls0.1/run_test.sh
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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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oid sha256:c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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size 2464616
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test_results.json
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{
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"eval_accuracy": 0.8627727031707764,
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"eval_loss": 0.46840450167655945,
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"eval_runtime": 8.8065,
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"eval_samples_per_second": 161.359,
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"eval_steps_per_second": 10.106,
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"test_samples": 1421
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}
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tokenizer.json
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tokenizer_config.json
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{
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"bos_token": "[CLS]",
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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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"name_or_path": "microsoft/deberta-v3-large",
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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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"special_tokens_map_file": null,
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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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trainer_state.json
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