---
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: 0.8564
- Accuracy: 0.8761
- F1: 0.8755
- Precision: 0.8892
- Recall: 0.8761

## 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 OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3029        | 1.0   | 339  | 1.1999          | 0.5634   | 0.4575 | 0.4881    | 0.5634 |
| 1.0073        | 2.0   | 678  | 0.9380          | 0.7168   | 0.6836 | 0.7627    | 0.7168 |
| 0.8519        | 3.0   | 1017 | 0.8564          | 0.8761   | 0.8755 | 0.8892    | 0.8761 |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.7.1+cpu
- Datasets 4.2.0
- Tokenizers 0.22.1