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# N_bert_agnews_padding20model

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: 0.5675
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.178         | 1.0   | 7500   | 0.2016          | 0.9387   |
| 0.1359        | 2.0   | 15000  | 0.1994          | 0.9463   |
| 0.1199        | 3.0   | 22500  | 0.2296          | 0.9439   |
| 0.0893        | 4.0   | 30000  | 0.2822          | 0.9433   |
| 0.0632        | 5.0   | 37500  | 0.2953          | 0.9384   |
| 0.0441        | 6.0   | 45000  | 0.3583          | 0.9458   |
| 0.0337        | 7.0   | 52500  | 0.3966          | 0.9433   |
| 0.0287        | 8.0   | 60000  | 0.4296          | 0.9434   |
| 0.0241        | 9.0   | 67500  | 0.4442          | 0.9414   |
| 0.0118        | 10.0  | 75000  | 0.5066          | 0.9405   |
| 0.0166        | 11.0  | 82500  | 0.4644          | 0.94     |
| 0.0118        | 12.0  | 90000  | 0.4789          | 0.9409   |
| 0.0115        | 13.0  | 97500  | 0.5151          | 0.9443   |
| 0.0075        | 14.0  | 105000 | 0.4855          | 0.9458   |
| 0.007         | 15.0  | 112500 | 0.5377          | 0.9430   |
| 0.0058        | 16.0  | 120000 | 0.5308          | 0.9458   |
| 0.0024        | 17.0  | 127500 | 0.5328          | 0.9451   |
| 0.0014        | 18.0  | 135000 | 0.5569          | 0.9462   |
| 0.0023        | 19.0  | 142500 | 0.5646          | 0.9480   |
| 0.0019        | 20.0  | 150000 | 0.5675          | 0.9482   |


### 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_padding20model", "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 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