---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERTHateSpeechClassification
  results: []
---

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

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9543
- Accuracy: 0.8297

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5186        | 1.0   | 569  | 0.4308          | 0.8187   |
| 0.3416        | 2.0   | 1138 | 0.3868          | 0.8286   |
| 0.2578        | 3.0   | 1707 | 0.4636          | 0.8385   |
| 0.1757        | 4.0   | 2276 | 0.6496          | 0.8418   |
| 0.1286        | 5.0   | 2845 | 0.9543          | 0.8297   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0