End of training
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README.md
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---
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base_model: allenai/cs_roberta_base
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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: cs_roberta_base-1
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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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# cs_roberta_base-1
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This model is a fine-tuned version of [allenai/cs_roberta_base](https://huggingface.co/allenai/cs_roberta_base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3743
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- Accuracy: 0.8905
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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: 46
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- eval_batch_size: 46
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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: 10
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- mixed_precision_training: Native AMP
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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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| 1.3782 | 1.0 | 1044 | 0.9372 | 0.79 |
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| 0.7908 | 2.0 | 2088 | 0.6508 | 0.8418 |
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| 0.5942 | 3.0 | 3132 | 0.5638 | 0.8604 |
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| 0.4986 | 4.0 | 4176 | 0.4780 | 0.8707 |
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| 0.4301 | 5.0 | 5220 | 0.4408 | 0.8794 |
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| 0.3798 | 6.0 | 6264 | 0.4103 | 0.8821 |
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| 0.3388 | 7.0 | 7308 | 0.3938 | 0.8842 |
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| 0.3082 | 8.0 | 8352 | 0.3821 | 0.8909 |
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| 0.2842 | 9.0 | 9396 | 0.3852 | 0.887 |
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| 0.2674 | 10.0 | 10440 | 0.3743 | 0.8905 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.0
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- Tokenizers 0.15.0
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