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--- |
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license: cc-by-4.0 |
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library_name: peft |
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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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base_model: deepset/roberta-base-squad2 |
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model-index: |
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- name: STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-test-111-with-higher-r-mid |
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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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# STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-test-111-with-higher-r-mid |
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This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0593 |
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- Accuracy: 0.5627 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 30 |
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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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| No log | 1.0 | 297 | 1.2901 | 0.4489 | |
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| 1.2919 | 2.0 | 594 | 1.1817 | 0.4931 | |
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| 1.2919 | 3.0 | 891 | 1.1639 | 0.4996 | |
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| 1.0546 | 4.0 | 1188 | 1.1222 | 0.5221 | |
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| 1.0546 | 5.0 | 1485 | 1.1199 | 0.5279 | |
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| 0.9971 | 6.0 | 1782 | 1.1256 | 0.5257 | |
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| 0.9606 | 7.0 | 2079 | 1.0944 | 0.5439 | |
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| 0.9606 | 8.0 | 2376 | 1.1414 | 0.5323 | |
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| 0.9423 | 9.0 | 2673 | 1.0932 | 0.5337 | |
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| 0.9423 | 10.0 | 2970 | 1.1029 | 0.5468 | |
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| 0.9171 | 11.0 | 3267 | 1.0914 | 0.5330 | |
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| 0.9069 | 12.0 | 3564 | 1.0582 | 0.5533 | |
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| 0.9069 | 13.0 | 3861 | 1.0677 | 0.5526 | |
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| 0.8954 | 14.0 | 4158 | 1.0817 | 0.5460 | |
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| 0.8954 | 15.0 | 4455 | 1.0703 | 0.5526 | |
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| 0.8926 | 16.0 | 4752 | 1.0724 | 0.5555 | |
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| 0.8845 | 17.0 | 5049 | 1.0583 | 0.5591 | |
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| 0.8845 | 18.0 | 5346 | 1.0749 | 0.5620 | |
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| 0.8666 | 19.0 | 5643 | 1.0559 | 0.5518 | |
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| 0.8666 | 20.0 | 5940 | 1.0660 | 0.5591 | |
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| 0.8602 | 21.0 | 6237 | 1.0620 | 0.5533 | |
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| 0.8582 | 22.0 | 6534 | 1.0891 | 0.5591 | |
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| 0.8582 | 23.0 | 6831 | 1.0565 | 0.5656 | |
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| 0.8539 | 24.0 | 7128 | 1.0680 | 0.5591 | |
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| 0.8539 | 25.0 | 7425 | 1.0556 | 0.5620 | |
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| 0.8551 | 26.0 | 7722 | 1.0605 | 0.5569 | |
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| 0.8512 | 27.0 | 8019 | 1.0560 | 0.5635 | |
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| 0.8512 | 28.0 | 8316 | 1.0552 | 0.5627 | |
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| 0.8505 | 29.0 | 8613 | 1.0599 | 0.5613 | |
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| 0.8505 | 30.0 | 8910 | 1.0593 | 0.5627 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
