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# N_roberta_agnews_padding90model

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: 0.5490
- Accuracy: 0.9482

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.1972        | 1.0   | 7500   | 0.2055          | 0.9412   |
| 0.1723        | 2.0   | 15000  | 0.1951          | 0.9463   |
| 0.1529        | 3.0   | 22500  | 0.2150          | 0.9461   |
| 0.1256        | 4.0   | 30000  | 0.2472          | 0.9457   |
| 0.1092        | 5.0   | 37500  | 0.2550          | 0.9459   |
| 0.0729        | 6.0   | 45000  | 0.2972          | 0.9479   |
| 0.0801        | 7.0   | 52500  | 0.3123          | 0.9453   |
| 0.058         | 8.0   | 60000  | 0.3705          | 0.9463   |
| 0.0463        | 9.0   | 67500  | 0.3698          | 0.9438   |
| 0.0387        | 10.0  | 75000  | 0.3702          | 0.9495   |
| 0.0299        | 11.0  | 82500  | 0.4177          | 0.9474   |
| 0.0235        | 12.0  | 90000  | 0.4637          | 0.9432   |
| 0.0172        | 13.0  | 97500  | 0.4843          | 0.9464   |
| 0.0144        | 14.0  | 105000 | 0.4647          | 0.9483   |
| 0.0147        | 15.0  | 112500 | 0.4965          | 0.9468   |
| 0.0124        | 16.0  | 120000 | 0.5153          | 0.9470   |
| 0.006         | 17.0  | 127500 | 0.5196          | 0.9483   |
| 0.0047        | 18.0  | 135000 | 0.5287          | 0.9480   |
| 0.0056        | 19.0  | 142500 | 0.5443          | 0.9480   |
| 0.0012        | 20.0  | 150000 | 0.5490          | 0.9482   |


### 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_padding90model", "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": 0.9481578947368421, "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