---
base_model: google/muril-large-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Muril-base-finetune-Tamil-qc
  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. -->

# Muril-base-finetune-Tamil-qc

This model is a fine-tuned version of [google/muril-large-cased](https://huggingface.co/google/muril-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7585
- Precision: 0.8899
- Recall: 0.8887
- Accuracy: 0.8887
- F1-score: 0.8892

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.7778        | 1.0   | 155  | 0.4237          | 0.8573    | 0.8664 | 0.8664   | 0.8605   |
| 0.2769        | 2.0   | 310  | 0.3965          | 0.8789    | 0.8765 | 0.8765   | 0.8769   |
| 0.1657        | 3.0   | 465  | 0.4423          | 0.8889    | 0.8866 | 0.8866   | 0.8870   |
| 0.0975        | 4.0   | 620  | 0.5887          | 0.8824    | 0.8785 | 0.8785   | 0.8798   |
| 0.067         | 5.0   | 775  | 0.6212          | 0.8882    | 0.8846 | 0.8846   | 0.8858   |
| 0.034         | 6.0   | 930  | 0.6018          | 0.8948    | 0.8927 | 0.8927   | 0.8934   |
| 0.0249        | 7.0   | 1085 | 0.7035          | 0.8902    | 0.8887 | 0.8887   | 0.8893   |
| 0.0206        | 8.0   | 1240 | 0.7113          | 0.8936    | 0.8927 | 0.8927   | 0.8931   |
| 0.0122        | 9.0   | 1395 | 0.7400          | 0.8899    | 0.8887 | 0.8887   | 0.8892   |
| 0.0043        | 10.0  | 1550 | 0.7585          | 0.8899    | 0.8887 | 0.8887   | 0.8892   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2