README.md

---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-finetuned_ADEs_SonatafyAI
  results: []
---

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# bert-base-cased-finetuned_ADEs_SonatafyAI

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: 0.3543
- Precision: 0.3857
- Recall: 0.4776
- F1: 0.4268
- Accuracy: 0.8554

## 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-07
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5644        | 1.0   | 640  | 0.4536          | 0.2717    | 0.3148 | 0.2916 | 0.8285   |
| 0.4695        | 2.0   | 1280 | 0.3977          | 0.3292    | 0.4109 | 0.3656 | 0.8462   |
| 0.4253        | 3.0   | 1920 | 0.3717          | 0.3653    | 0.4536 | 0.4047 | 0.8509   |
| 0.3872        | 4.0   | 2560 | 0.3578          | 0.3747    | 0.4623 | 0.4139 | 0.8544   |
| 0.3758        | 5.0   | 3200 | 0.3543          | 0.3857    | 0.4776 | 0.4268 | 0.8554   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1