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# bert-base-uncased-finetuned-stationary-epoch-update

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: 0.4848
- Accuracy: 0.81
- F1: 0.8070

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5929        | 1.0   | 38   | 0.4930          | 0.7567   | 0.7336 |
| 0.4451        | 2.0   | 76   | 0.4422          | 0.8067   | 0.8076 |
| 0.3475        | 3.0   | 114  | 0.4470          | 0.81     | 0.8115 |
| 0.2764        | 4.0   | 152  | 0.5021          | 0.78     | 0.7693 |
| 0.2205        | 5.0   | 190  | 0.4848          | 0.81     | 0.8070 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-finetuned-stationary-epoch-update", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us