---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-base-cased

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2087
- Precision: 0.3464
- Recall: 0.4037
- F1: 0.3728
- Accuracy: 0.9315

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 88   | 0.2396          | 0.2519    | 0.2699 | 0.2606 | 0.9228   |
| No log        | 2.0   | 176  | 0.2117          | 0.3490    | 0.3397 | 0.3443 | 0.9315   |
| No log        | 3.0   | 264  | 0.2087          | 0.3464    | 0.4037 | 0.3728 | 0.9315   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.0
- Datasets 2.14.7
- Tokenizers 0.19.1