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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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base_model: distilroberta-base |
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model-index: |
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- name: distilroberta-base-finegrain |
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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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# distilroberta-base-finegrain |
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3713 |
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- F1: 0.9129 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.3944 | 1.0 | 844 | 0.3998 | 0.9163 | |
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| 0.3886 | 2.0 | 1688 | 0.4020 | 0.9163 | |
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| 0.3899 | 3.0 | 2532 | 0.3423 | 0.9163 | |
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| 0.4026 | 4.0 | 3376 | 0.3837 | 0.9163 | |
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| 0.3911 | 5.0 | 4220 | 0.3492 | 0.9163 | |
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| 0.3856 | 6.0 | 5064 | 0.3504 | 0.9163 | |
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| 0.4058 | 7.0 | 5908 | 0.3682 | 0.9163 | |
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| 0.4057 | 8.0 | 6752 | 0.3767 | 0.9163 | |
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| 0.3807 | 9.0 | 7596 | 0.3519 | 0.9163 | |
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| 0.394 | 10.0 | 8440 | 0.3603 | 0.9163 | |
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| 0.39 | 11.0 | 9284 | 0.3630 | 0.9163 | |
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| 0.3945 | 12.0 | 10128 | 0.3846 | 0.9163 | |
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| 0.3948 | 13.0 | 10972 | 0.3711 | 0.9163 | |
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| 0.3981 | 14.0 | 11816 | 0.3516 | 0.9163 | |
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| 0.4144 | 15.0 | 12660 | 0.3526 | 0.9163 | |
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| 0.3999 | 16.0 | 13504 | 0.3560 | 0.9163 | |
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| 0.376 | 17.0 | 14348 | 0.3671 | 0.9163 | |
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| 0.412 | 18.0 | 15192 | 0.3630 | 0.9163 | |
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| 0.389 | 19.0 | 16036 | 0.3669 | 0.9136 | |
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| 0.374 | 20.0 | 16880 | 0.3713 | 0.9129 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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