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# quiz3_roberta

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: 0.5310
- Accuracy: 0.7533
- F1: 0.7843
- Precision: 0.8056
- Recall: 0.7642

## 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: 1e-06
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 307  | 0.6703          | 0.5871   | 0.7399 | 0.5871    | 1.0    |
| 0.6773        | 2.0   | 614  | 0.5770          | 0.6783   | 0.7659 | 0.6687    | 0.8960 |
| 0.6773        | 3.0   | 921  | 0.5382          | 0.7549   | 0.7870 | 0.8035    | 0.7712 |
| 0.5847        | 4.0   | 1228 | 0.5324          | 0.7516   | 0.7823 | 0.8059    | 0.7601 |
| 0.5513        | 5.0   | 1535 | 0.5310          | 0.7533   | 0.7843 | 0.8056    | 0.7642 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "roberta-base", "model-index": [{"name": "quiz3_roberta", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us