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# N_bert_agnews_padding100model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5818
- Accuracy: 0.945

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.1815        | 1.0   | 7500   | 0.1891          | 0.9421   |
| 0.1362        | 2.0   | 15000  | 0.2013          | 0.9446   |
| 0.1152        | 3.0   | 22500  | 0.2381          | 0.9443   |
| 0.0809        | 4.0   | 30000  | 0.2646          | 0.9453   |
| 0.0598        | 5.0   | 37500  | 0.3089          | 0.9425   |
| 0.0405        | 6.0   | 45000  | 0.3708          | 0.9391   |
| 0.0387        | 7.0   | 52500  | 0.3904          | 0.9418   |
| 0.0212        | 8.0   | 60000  | 0.4448          | 0.9432   |
| 0.0225        | 9.0   | 67500  | 0.4465          | 0.9429   |
| 0.0145        | 10.0  | 75000  | 0.4374          | 0.9445   |
| 0.017         | 11.0  | 82500  | 0.4895          | 0.9438   |
| 0.0091        | 12.0  | 90000  | 0.4848          | 0.9443   |
| 0.0128        | 13.0  | 97500  | 0.4764          | 0.9455   |
| 0.0044        | 14.0  | 105000 | 0.5263          | 0.9449   |
| 0.0018        | 15.0  | 112500 | 0.5252          | 0.9447   |
| 0.0017        | 16.0  | 120000 | 0.5324          | 0.9468   |
| 0.001         | 17.0  | 127500 | 0.5503          | 0.9457   |
| 0.0006        | 18.0  | 135000 | 0.5748          | 0.9458   |
| 0.0002        | 19.0  | 142500 | 0.5715          | 0.9459   |
| 0.0015        | 20.0  | 150000 | 0.5818          | 0.945    |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ag_news"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "N_bert_agnews_padding100model", "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": 0.945, "name": "Accuracy"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer dataset:ag_news base_model:bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us