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# N_roberta_agnews_padding0model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5421
- Accuracy: 0.9501

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.1929        | 1.0   | 7500   | 0.2180          | 0.9363   |
| 0.1646        | 2.0   | 15000  | 0.2092          | 0.9455   |
| 0.1502        | 3.0   | 22500  | 0.2136          | 0.9478   |
| 0.1217        | 4.0   | 30000  | 0.2395          | 0.9476   |
| 0.1008        | 5.0   | 37500  | 0.2357          | 0.9501   |
| 0.0789        | 6.0   | 45000  | 0.3286          | 0.9420   |
| 0.0625        | 7.0   | 52500  | 0.3378          | 0.9439   |
| 0.0546        | 8.0   | 60000  | 0.4044          | 0.9443   |
| 0.0434        | 9.0   | 67500  | 0.4361          | 0.9412   |
| 0.0321        | 10.0  | 75000  | 0.4044          | 0.9453   |
| 0.0254        | 11.0  | 82500  | 0.4670          | 0.9455   |
| 0.0302        | 12.0  | 90000  | 0.4657          | 0.9438   |
| 0.0224        | 13.0  | 97500  | 0.4942          | 0.9432   |
| 0.0085        | 14.0  | 105000 | 0.5315          | 0.9449   |
| 0.0053        | 15.0  | 112500 | 0.5283          | 0.9455   |
| 0.01          | 16.0  | 120000 | 0.5004          | 0.9466   |
| 0.0061        | 17.0  | 127500 | 0.5430          | 0.9458   |
| 0.0042        | 18.0  | 135000 | 0.5116          | 0.9486   |
| 0.0034        | 19.0  | 142500 | 0.5379          | 0.9491   |
| 0.0022        | 20.0  | 150000 | 0.5421          | 0.9501   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["ag_news"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "N_roberta_agnews_padding0model", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "ag_news", "type": "ag_news", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9501315789473684, "name": "Accuracy"}]}]}]}
transformers pytorch roberta text-classification generated_from_trainer dataset:ag_news base_model:roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us