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--- |
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license: mit |
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base_model: roberta-large |
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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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model-index: |
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- name: roberta-large-sst-2-64-13-30 |
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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-large-sst-2-64-13-30 |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8764 |
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- Accuracy: 0.8828 |
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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: 1.5e-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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- lr_scheduler_warmup_steps: 5 |
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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 | 4 | 0.7179 | 0.5 | |
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| No log | 2.0 | 8 | 0.6981 | 0.5312 | |
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| 0.717 | 3.0 | 12 | 0.6948 | 0.4688 | |
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| 0.717 | 4.0 | 16 | 0.7043 | 0.4453 | |
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| 0.6986 | 5.0 | 20 | 0.6971 | 0.4688 | |
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| 0.6986 | 6.0 | 24 | 0.7705 | 0.5156 | |
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| 0.6986 | 7.0 | 28 | 0.7463 | 0.625 | |
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| 0.6087 | 8.0 | 32 | 0.7016 | 0.6172 | |
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| 0.6087 | 9.0 | 36 | 0.5869 | 0.7656 | |
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| 0.5365 | 10.0 | 40 | 0.5156 | 0.8047 | |
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| 0.5365 | 11.0 | 44 | 0.4578 | 0.8203 | |
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| 0.5365 | 12.0 | 48 | 0.3511 | 0.9141 | |
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| 0.3599 | 13.0 | 52 | 0.3583 | 0.8828 | |
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| 0.3599 | 14.0 | 56 | 0.3759 | 0.8828 | |
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| 0.1271 | 15.0 | 60 | 0.4324 | 0.8906 | |
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| 0.1271 | 16.0 | 64 | 0.4806 | 0.8984 | |
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| 0.1271 | 17.0 | 68 | 0.5256 | 0.875 | |
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| 0.0516 | 18.0 | 72 | 0.6432 | 0.8906 | |
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| 0.0516 | 19.0 | 76 | 0.6976 | 0.875 | |
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| 0.0034 | 20.0 | 80 | 0.8148 | 0.875 | |
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| 0.0034 | 21.0 | 84 | 0.8401 | 0.8828 | |
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| 0.0034 | 22.0 | 88 | 0.8721 | 0.8828 | |
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| 0.0467 | 23.0 | 92 | 0.8001 | 0.8906 | |
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| 0.0467 | 24.0 | 96 | 0.8580 | 0.8828 | |
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| 0.0005 | 25.0 | 100 | 0.8849 | 0.875 | |
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| 0.0005 | 26.0 | 104 | 0.9024 | 0.875 | |
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| 0.0005 | 27.0 | 108 | 0.9125 | 0.875 | |
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| 0.0005 | 28.0 | 112 | 0.8686 | 0.8828 | |
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| 0.0005 | 29.0 | 116 | 0.8764 | 0.8828 | |
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| 0.0231 | 30.0 | 120 | 0.8764 | 0.8828 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.4.0 |
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- Tokenizers 0.13.3 |
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