---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: bert-because-trainer-oversample
  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-because-trainer-oversample

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3274
- Accuracy: 0.8972
- F1: 0.8299
- Recall: 0.8342
- Precision: 0.8256

## 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: 5e-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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.6383        | 0.07  | 25   | 0.5128          | 0.7461   | 0.2882 | 0.1710 | 0.9167    |
| 0.5933        | 0.15  | 50   | 0.5335          | 0.7352   | 0.6545 | 0.8342 | 0.5385    |
| 0.4774        | 0.22  | 75   | 0.4369          | 0.8131   | 0.5804 | 0.4301 | 0.8925    |
| 0.4801        | 0.3   | 100  | 0.3538          | 0.8458   | 0.7429 | 0.7409 | 0.7448    |
| 0.3765        | 0.37  | 125  | 0.3890          | 0.8536   | 0.7267 | 0.6477 | 0.8278    |
| 0.3411        | 0.45  | 150  | 0.4052          | 0.8474   | 0.7710 | 0.8549 | 0.7021    |
| 0.2802        | 0.52  | 175  | 0.3509          | 0.8660   | 0.7701 | 0.7461 | 0.7956    |
| 0.2558        | 0.59  | 200  | 0.4704          | 0.8629   | 0.7179 | 0.5803 | 0.9412    |
| 0.4603        | 0.67  | 225  | 0.3298          | 0.8801   | 0.7968 | 0.7824 | 0.8118    |
| 0.3211        | 0.74  | 250  | 0.3053          | 0.8925   | 0.8189 | 0.8083 | 0.8298    |
| 0.2475        | 0.82  | 275  | 0.3052          | 0.8879   | 0.8209 | 0.8549 | 0.7895    |
| 0.2644        | 0.89  | 300  | 0.3688          | 0.8910   | 0.8077 | 0.7617 | 0.8596    |
| 0.3206        | 0.96  | 325  | 0.3332          | 0.8988   | 0.8320 | 0.8342 | 0.8299    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.1
- Datasets 2.19.1
- Tokenizers 0.15.1