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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/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: fine_tuned_main_raid |
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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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# fine_tuned_main_raid |
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This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0284 |
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- Accuracy: 0.9931 |
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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: 2e-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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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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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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| 0.3359 | 0.1018 | 100 | 0.1977 | 0.9703 | |
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| 0.17 | 0.2037 | 200 | 0.3161 | 0.9542 | |
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| 0.1525 | 0.3055 | 300 | 0.0936 | 0.9828 | |
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| 0.0874 | 0.4073 | 400 | 0.0900 | 0.9863 | |
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| 0.097 | 0.5092 | 500 | 0.0992 | 0.9863 | |
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| 0.0874 | 0.6110 | 600 | 0.1275 | 0.9851 | |
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| 0.0763 | 0.7128 | 700 | 0.1173 | 0.9840 | |
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| 0.1067 | 0.8147 | 800 | 0.0585 | 0.9874 | |
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| 0.0646 | 0.9165 | 900 | 0.0358 | 0.9943 | |
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| 0.0338 | 1.0183 | 1000 | 0.0413 | 0.9943 | |
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| 0.0463 | 1.1202 | 1100 | 0.0311 | 0.9943 | |
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| 0.0683 | 1.2220 | 1200 | 0.0473 | 0.9920 | |
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| 0.0315 | 1.3238 | 1300 | 0.0374 | 0.9931 | |
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| 0.0251 | 1.4257 | 1400 | 0.0335 | 0.9954 | |
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| 0.0238 | 1.5275 | 1500 | 0.0481 | 0.9931 | |
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| 0.0105 | 1.6293 | 1600 | 0.0555 | 0.9931 | |
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| 0.063 | 1.7312 | 1700 | 0.0343 | 0.9931 | |
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| 0.0389 | 1.8330 | 1800 | 0.0355 | 0.9931 | |
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| 0.0463 | 1.9348 | 1900 | 0.0584 | 0.9897 | |
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| 0.0075 | 2.0367 | 2000 | 0.0284 | 0.9931 | |
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| 0.0036 | 2.1385 | 2100 | 0.1225 | 0.9760 | |
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| 0.0062 | 2.2403 | 2200 | 0.0333 | 0.9943 | |
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| 0.0136 | 2.3422 | 2300 | 0.0379 | 0.9920 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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