---
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: 0.6739
- Precision: 0.9145
- Recall: 0.9130
- Accuracy: 0.9130
- F1-score: 0.9135

## 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: 5e-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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.6155        | 1.0   | 155  | 0.3583          | 0.8905    | 0.8887 | 0.8887   | 0.8889   |
| 0.2625        | 2.0   | 310  | 0.4334          | 0.8741    | 0.8623 | 0.8623   | 0.8618   |
| 0.1603        | 3.0   | 465  | 0.4511          | 0.8890    | 0.8866 | 0.8866   | 0.8862   |
| 0.0885        | 4.0   | 620  | 0.4819          | 0.9087    | 0.9028 | 0.9028   | 0.9034   |
| 0.0541        | 5.0   | 775  | 0.6202          | 0.8934    | 0.8927 | 0.8927   | 0.8929   |
| 0.0207        | 6.0   | 930  | 0.6179          | 0.9117    | 0.9089 | 0.9089   | 0.9093   |
| 0.0152        | 7.0   | 1085 | 0.6444          | 0.9060    | 0.9049 | 0.9049   | 0.9053   |
| 0.0057        | 8.0   | 1240 | 0.6534          | 0.9120    | 0.9109 | 0.9109   | 0.9114   |
| 0.0039        | 9.0   | 1395 | 0.6734          | 0.9146    | 0.9130 | 0.9130   | 0.9136   |
| 0.0039        | 10.0  | 1550 | 0.6739          | 0.9145    | 0.9130 | 0.9130   | 0.9135   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1