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# claim-classifier

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3432
- Accuracy: 0.8889

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.048         | 1.0   | 562  | 0.3966          | 0.8669   |
| 0.3896        | 2.0   | 1124 | 0.4440          | 0.8669   |
| 0.4783        | 3.0   | 1686 | 0.3893          | 0.8699   |
| 0.4792        | 4.0   | 2248 | 0.4019          | 0.8689   |
| 1.2405        | 5.0   | 2810 | 0.3883          | 0.8729   |
| 0.0996        | 6.0   | 3372 | 0.3673          | 0.8669   |
| 0.4833        | 7.0   | 3934 | 0.3873          | 0.8759   |
| 0.2461        | 8.0   | 4496 | 0.3646          | 0.8659   |
| 0.0977        | 9.0   | 5058 | 0.3432          | 0.8889   |
| 0.0682        | 10.0  | 5620 | 0.3458          | 0.8919   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.8.1
- Datasets 2.13.2
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "claim-classifier", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us