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--- |
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license: mit |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: roberta-base |
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model-index: |
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- name: roberta-base_PrefixTuning_lr5e-05_bs4_epoch20_wd0.01 |
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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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# roberta-base_PrefixTuning_lr5e-05_bs4_epoch20_wd0.01 |
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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: 14.4579 |
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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: 4 |
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- eval_batch_size: 8 |
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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: 500 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 15.4862 | 1.0 | 157 | 20.8478 | |
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| 14.9721 | 2.0 | 314 | 20.7345 | |
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| 15.0553 | 3.0 | 471 | 20.5177 | |
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| 14.4627 | 4.0 | 628 | 20.2344 | |
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| 14.0788 | 5.0 | 785 | 19.9480 | |
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| 13.2092 | 6.0 | 942 | 19.6334 | |
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| 13.0141 | 7.0 | 1099 | 19.2349 | |
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| 12.5052 | 8.0 | 1256 | 18.7395 | |
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| 11.8852 | 9.0 | 1413 | 18.2110 | |
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| 11.889 | 10.0 | 1570 | 17.7415 | |
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| 11.2937 | 11.0 | 1727 | 17.3058 | |
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| 11.0163 | 12.0 | 1884 | 16.8580 | |
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| 10.8939 | 13.0 | 2041 | 16.3684 | |
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| 10.8183 | 14.0 | 2198 | 15.9196 | |
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| 10.353 | 15.0 | 2355 | 15.5043 | |
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| 10.1386 | 16.0 | 2512 | 15.1272 | |
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| 9.9726 | 17.0 | 2669 | 14.8365 | |
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| 9.8421 | 18.0 | 2826 | 14.6183 | |
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| 9.9193 | 19.0 | 2983 | 14.4978 | |
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| 9.848 | 20.0 | 3140 | 14.4579 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
