---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: mbert-hatespeechdetection-tamil
  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. -->

# mbert-hatespeechdetection-tamil

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5521
- Accuracy: 0.8627
- F1: 0.8293

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.69          | 1.0   | 13   | 0.6642          | 0.6275   | 0.2963 |
| 0.6359        | 2.0   | 26   | 0.5405          | 0.7647   | 0.76   |
| 0.506         | 3.0   | 39   | 0.5011          | 0.7843   | 0.7843 |
| 0.3823        | 4.0   | 52   | 0.4513          | 0.8431   | 0.84   |
| 0.2723        | 5.0   | 65   | 0.3428          | 0.8627   | 0.8511 |
| 0.1862        | 6.0   | 78   | 0.3705          | 0.8431   | 0.8182 |
| 0.132         | 7.0   | 91   | 0.4117          | 0.8627   | 0.8511 |
| 0.0629        | 8.0   | 104  | 0.5471          | 0.8627   | 0.8293 |
| 0.0302        | 9.0   | 117  | 0.6216          | 0.8627   | 0.8293 |
| 0.0083        | 10.0  | 130  | 0.7940          | 0.8431   | 0.8000 |
| 0.038         | 11.0  | 143  | 0.7867          | 0.8627   | 0.8293 |
| 0.052         | 12.0  | 156  | 0.7889          | 0.8431   | 0.8182 |
| 0.0179        | 13.0  | 169  | 1.0893          | 0.8039   | 0.8    |
| 0.0032        | 14.0  | 182  | 0.9028          | 0.8627   | 0.8108 |
| 0.0021        | 15.0  | 195  | 0.8124          | 0.8431   | 0.7895 |
| 0.0018        | 16.0  | 208  | 0.6030          | 0.8627   | 0.8205 |
| 0.0014        | 17.0  | 221  | 0.9289          | 0.8235   | 0.8085 |
| 0.0015        | 18.0  | 234  | 0.6005          | 0.8824   | 0.8421 |
| 0.0013        | 19.0  | 247  | 0.5998          | 0.8824   | 0.8421 |
| 0.0012        | 20.0  | 260  | 0.5521          | 0.8627   | 0.8293 |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.21.2