---
library_name: transformers
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MuRILHateSpeechClassification
  results: []
---

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

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7371
- Accuracy: 0.8407

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5519        | 1.0   | 1137 | 0.4704          | 0.8110   |
| 0.4345        | 2.0   | 2274 | 0.4862          | 0.8198   |
| 0.3547        | 3.0   | 3411 | 0.4660          | 0.8473   |
| 0.2919        | 4.0   | 4548 | 0.6066          | 0.8440   |
| 0.2205        | 5.0   | 5685 | 0.6805          | 0.8429   |
| 0.1759        | 6.0   | 6822 | 0.7371          | 0.8407   |


### Framework versions

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