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# N_roberta_agnews_padding60model

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: 0.5823
- Accuracy: 0.9461

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.2028        | 1.0   | 7500   | 0.2106          | 0.9407   |
| 0.1643        | 2.0   | 15000  | 0.1864          | 0.9475   |
| 0.1536        | 3.0   | 22500  | 0.2135          | 0.9455   |
| 0.1243        | 4.0   | 30000  | 0.2261          | 0.9468   |
| 0.1045        | 5.0   | 37500  | 0.2428          | 0.9468   |
| 0.0861        | 6.0   | 45000  | 0.2795          | 0.9434   |
| 0.0767        | 7.0   | 52500  | 0.3035          | 0.9470   |
| 0.0532        | 8.0   | 60000  | 0.3571          | 0.9461   |
| 0.0532        | 9.0   | 67500  | 0.3586          | 0.9426   |
| 0.0342        | 10.0  | 75000  | 0.4128          | 0.9434   |
| 0.026         | 11.0  | 82500  | 0.4228          | 0.9470   |
| 0.0226        | 12.0  | 90000  | 0.4714          | 0.9434   |
| 0.0209        | 13.0  | 97500  | 0.4663          | 0.9458   |
| 0.0127        | 14.0  | 105000 | 0.4939          | 0.9436   |
| 0.0082        | 15.0  | 112500 | 0.4959          | 0.9483   |
| 0.0142        | 16.0  | 120000 | 0.5230          | 0.9461   |
| 0.0024        | 17.0  | 127500 | 0.5710          | 0.9445   |
| 0.0082        | 18.0  | 135000 | 0.5560          | 0.9459   |
| 0.0034        | 19.0  | 142500 | 0.5778          | 0.9462   |
| 0.0018        | 20.0  | 150000 | 0.5823          | 0.9461   |


### 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_padding60model", "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": 0.9460526315789474, "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