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# N_bert_agnews_padding0model

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: 0.5653
- Accuracy: 0.9476

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.1773        | 1.0   | 7500   | 0.1841          | 0.9433   |
| 0.1354        | 2.0   | 15000  | 0.2061          | 0.9463   |
| 0.1138        | 3.0   | 22500  | 0.2455          | 0.9428   |
| 0.0852        | 4.0   | 30000  | 0.2881          | 0.9429   |
| 0.0627        | 5.0   | 37500  | 0.3271          | 0.9433   |
| 0.0436        | 6.0   | 45000  | 0.3524          | 0.9441   |
| 0.034         | 7.0   | 52500  | 0.3977          | 0.9424   |
| 0.0251        | 8.0   | 60000  | 0.4291          | 0.9441   |
| 0.0205        | 9.0   | 67500  | 0.4399          | 0.9420   |
| 0.0167        | 10.0  | 75000  | 0.4574          | 0.9429   |
| 0.0218        | 11.0  | 82500  | 0.4979          | 0.9429   |
| 0.0119        | 12.0  | 90000  | 0.5000          | 0.9438   |
| 0.0112        | 13.0  | 97500  | 0.4856          | 0.9454   |
| 0.0054        | 14.0  | 105000 | 0.5294          | 0.9457   |
| 0.0039        | 15.0  | 112500 | 0.5418          | 0.9459   |
| 0.0024        | 16.0  | 120000 | 0.5065          | 0.9468   |
| 0.0011        | 17.0  | 127500 | 0.5511          | 0.9458   |
| 0.0013        | 18.0  | 135000 | 0.5411          | 0.9471   |
| 0.0002        | 19.0  | 142500 | 0.5555          | 0.9472   |
| 0.0005        | 20.0  | 150000 | 0.5653          | 0.9476   |


### 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_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": 0.9476315789473684, "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