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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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metrics: |
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- accuracy |
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base_model: FacebookAI/roberta-base |
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model-index: |
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- name: STS-Lora-Fine-Tuning-Capstone-roberta-base-filtered-150-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-filtered-150-with-higher-r-mid |
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7443 |
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- Accuracy: 0.6873 |
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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: 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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- 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 | 449 | 1.0408 | 0.4625 | |
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| 0.9593 | 2.0 | 898 | 1.0281 | 0.4981 | |
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| 0.9206 | 3.0 | 1347 | 0.9842 | 0.5225 | |
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| 0.8912 | 4.0 | 1796 | 0.9107 | 0.5693 | |
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| 0.8539 | 5.0 | 2245 | 0.8257 | 0.6273 | |
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| 0.8107 | 6.0 | 2694 | 0.8062 | 0.6685 | |
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| 0.779 | 7.0 | 3143 | 0.7672 | 0.6648 | |
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| 0.7797 | 8.0 | 3592 | 0.7709 | 0.6704 | |
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| 0.7649 | 9.0 | 4041 | 0.7509 | 0.6873 | |
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| 0.7649 | 10.0 | 4490 | 0.7376 | 0.6816 | |
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| 0.7527 | 11.0 | 4939 | 0.7360 | 0.6835 | |
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| 0.7526 | 12.0 | 5388 | 0.7493 | 0.6816 | |
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| 0.7476 | 13.0 | 5837 | 0.7421 | 0.6723 | |
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| 0.741 | 14.0 | 6286 | 0.7331 | 0.6929 | |
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| 0.7284 | 15.0 | 6735 | 0.7404 | 0.6854 | |
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| 0.7321 | 16.0 | 7184 | 0.7372 | 0.6798 | |
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| 0.7269 | 17.0 | 7633 | 0.7344 | 0.6816 | |
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| 0.7237 | 18.0 | 8082 | 0.7428 | 0.6723 | |
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| 0.7261 | 19.0 | 8531 | 0.7368 | 0.6854 | |
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| 0.7261 | 20.0 | 8980 | 0.7591 | 0.6704 | |
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| 0.715 | 21.0 | 9429 | 0.7434 | 0.6835 | |
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| 0.7088 | 22.0 | 9878 | 0.7504 | 0.6854 | |
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| 0.7228 | 23.0 | 10327 | 0.7500 | 0.6835 | |
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| 0.7127 | 24.0 | 10776 | 0.7583 | 0.6835 | |
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| 0.706 | 25.0 | 11225 | 0.7353 | 0.6948 | |
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| 0.7104 | 26.0 | 11674 | 0.7423 | 0.6891 | |
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| 0.7068 | 27.0 | 12123 | 0.7426 | 0.6910 | |
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| 0.7046 | 28.0 | 12572 | 0.7494 | 0.6873 | |
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| 0.7036 | 29.0 | 13021 | 0.7460 | 0.6910 | |
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| 0.7036 | 30.0 | 13470 | 0.7443 | 0.6873 | |
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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 |
