---
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Muril-base-finetune-Telugu-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-Telugu-qc

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6250
- Precision: 0.7716
- Recall: 0.7647
- Accuracy: 0.7647
- F1-score: 0.7587

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 1.7858        | 1.0   | 32   | 1.7821          | 0.0454    | 0.2130 | 0.2130   | 0.0748   |
| 1.7526        | 2.0   | 64   | 1.7539          | 0.1754    | 0.2860 | 0.2860   | 0.1866   |
| 1.7112        | 3.0   | 96   | 1.7232          | 0.3352    | 0.3043 | 0.3043   | 0.2168   |
| 1.6655        | 4.0   | 128  | 1.6832          | 0.7122    | 0.6166 | 0.6166   | 0.6194   |
| 1.6217        | 5.0   | 160  | 1.6496          | 0.7708    | 0.7688 | 0.7688   | 0.7629   |
| 1.5898        | 6.0   | 192  | 1.6431          | 0.7618    | 0.7424 | 0.7424   | 0.7379   |
| 1.5678        | 7.0   | 224  | 1.6285          | 0.7697    | 0.7627 | 0.7627   | 0.7565   |
| 1.5572        | 8.0   | 256  | 1.6250          | 0.7716    | 0.7647 | 0.7647   | 0.7587   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2