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# bert-base-uncased-finetuned-cda2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6474

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0558        | 1.0   | 407  | 1.8182          |
| 1.8924        | 2.0   | 814  | 1.7201          |
| 1.8353        | 3.0   | 1221 | 1.7211          |
| 1.7979        | 4.0   | 1628 | 1.6805          |
| 1.7721        | 5.0   | 2035 | 1.6345          |
| 1.7489        | 6.0   | 2442 | 1.6593          |
| 1.7305        | 7.0   | 2849 | 1.6600          |
| 1.7186        | 8.0   | 3256 | 1.6309          |
| 1.7053        | 9.0   | 3663 | 1.6647          |
| 1.6998        | 10.0  | 4070 | 1.6539          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-finetuned-cda2", "results": []}]}
transformers tensorboard safetensors bert fill-mask generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us