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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: micro_base_help_tapt_pretrain_model |
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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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# micro_base_help_tapt_pretrain_model |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5916 |
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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: 0.0001 |
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- train_batch_size: 21 |
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- eval_batch_size: 21 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 42 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.9109 | 0.99 | 40 | 1.6849 | |
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| 1.7421 | 2.0 | 81 | 1.6620 | |
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| 1.7411 | 2.99 | 121 | 1.6333 | |
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| 1.6441 | 4.0 | 162 | 1.6306 | |
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| 1.6337 | 4.99 | 202 | 1.6137 | |
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| 1.5774 | 6.0 | 243 | 1.6343 | |
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| 1.5997 | 6.99 | 283 | 1.5931 | |
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| 1.5196 | 8.0 | 324 | 1.6018 | |
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| 1.5416 | 8.99 | 364 | 1.5994 | |
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| 1.4819 | 10.0 | 405 | 1.5886 | |
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| 1.5079 | 10.99 | 445 | 1.5938 | |
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| 1.455 | 12.0 | 486 | 1.5699 | |
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| 1.4718 | 12.99 | 526 | 1.5947 | |
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| 1.4157 | 14.0 | 567 | 1.5920 | |
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| 1.4369 | 14.99 | 607 | 1.5879 | |
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| 1.3733 | 16.0 | 648 | 1.5745 | |
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| 1.4017 | 16.99 | 688 | 1.6000 | |
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| 1.3601 | 18.0 | 729 | 1.5830 | |
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| 1.3602 | 18.99 | 769 | 1.5846 | |
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| 1.3152 | 20.0 | 810 | 1.5940 | |
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| 1.3437 | 20.99 | 850 | 1.5942 | |
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| 1.2904 | 22.0 | 891 | 1.5787 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.15.2 |
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