---
library_name: transformers
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

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: 0.3232
- Accuracy: 0.8957
- F1: 0.8913
- Precision: 0.8856
- Recall: 0.8970

## 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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4738        | 1.0   | 275  | 0.4001          | 0.8793   | 0.8768 | 0.8537    | 0.9013 |
| 0.3356        | 2.0   | 550  | 0.3046          | 0.9039   | 0.8967 | 0.9189    | 0.8755 |
| 0.2047        | 3.0   | 825  | 0.3029          | 0.9059   | 0.9013 | 0.9013    | 0.9013 |
| 0.2142        | 4.0   | 1100 | 0.3232          | 0.8957   | 0.8913 | 0.8856    | 0.8970 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2