---
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-eval
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-eval

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2288
- F1: 0.7837
- Roc Auc: 0.8490
- Accuracy: 0.3137

## 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: 8
- eval_batch_size: 8
- 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 | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4067        | 1.0   | 751  | 0.2930          | 0.7145 | 0.7911  | 0.2188   |
| 0.2483        | 2.0   | 1502 | 0.2528          | 0.7493 | 0.8167  | 0.2777   |
| 0.1993        | 3.0   | 2253 | 0.2323          | 0.7772 | 0.8406  | 0.3067   |
| 0.1468        | 4.0   | 3004 | 0.2288          | 0.7837 | 0.8490  | 0.3137   |
| 0.1238        | 5.0   | 3755 | 0.2287          | 0.7837 | 0.8509  | 0.3217   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3