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# cs_roberta_base-1

This model is a fine-tuned version of [allenai/cs_roberta_base](https://huggingface.co/allenai/cs_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3743
- Accuracy: 0.8905

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 46
- eval_batch_size: 46
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3782        | 1.0   | 1044  | 0.9372          | 0.79     |
| 0.7908        | 2.0   | 2088  | 0.6508          | 0.8418   |
| 0.5942        | 3.0   | 3132  | 0.5638          | 0.8604   |
| 0.4986        | 4.0   | 4176  | 0.4780          | 0.8707   |
| 0.4301        | 5.0   | 5220  | 0.4408          | 0.8794   |
| 0.3798        | 6.0   | 6264  | 0.4103          | 0.8821   |
| 0.3388        | 7.0   | 7308  | 0.3938          | 0.8842   |
| 0.3082        | 8.0   | 8352  | 0.3821          | 0.8909   |
| 0.2842        | 9.0   | 9396  | 0.3852          | 0.887    |
| 0.2674        | 10.0  | 10440 | 0.3743          | 0.8905   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "allenai/cs_roberta_base", "model-index": [{"name": "cs_roberta_base-1", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:allenai/cs_roberta_base autotrain_compatible endpoints_compatible region:us