---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: summerschool-bert-hate
  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. -->

# summerschool-bert-hate

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4316
- Accuracy: 0.5118
- F1: 0.4331

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5997        | 0.1776 | 100  | 0.5804          | 0.699    | 0.6939 |
| 0.5313        | 0.3552 | 200  | 0.5262          | 0.731    | 0.7310 |
| 0.4578        | 0.5329 | 300  | 0.5004          | 0.756    | 0.7557 |
| 0.4562        | 0.7105 | 400  | 0.4935          | 0.762    | 0.7630 |
| 0.411         | 0.8881 | 500  | 0.4921          | 0.757    | 0.7579 |
| 0.3869        | 1.0657 | 600  | 0.4913          | 0.765    | 0.7661 |
| 0.323         | 1.2433 | 700  | 0.5352          | 0.758    | 0.7593 |
| 0.3074        | 1.4210 | 800  | 0.5124          | 0.766    | 0.7669 |
| 0.3043        | 1.5986 | 900  | 0.5107          | 0.764    | 0.7647 |
| 0.3193        | 1.7762 | 1000 | 0.5056          | 0.769    | 0.7701 |
| 0.3324        | 1.9538 | 1100 | 0.4894          | 0.769    | 0.7700 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1