---
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: temp_assamese
  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. -->

# temp_assamese

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: 1.4149
- Accuracy: 0.7014

## 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: 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: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.2163        | 0.1409 | 2000  | 1.8646          | 0.6320   |
| 1.9456        | 0.2818 | 4000  | 1.7492          | 0.6495   |
| 1.8391        | 0.4227 | 6000  | 1.6770          | 0.6606   |
| 1.7704        | 0.5637 | 8000  | 1.6166          | 0.6707   |
| 1.7213        | 0.7046 | 10000 | 1.5818          | 0.6759   |
| 1.6802        | 0.8455 | 12000 | 1.5403          | 0.6820   |
| 1.6432        | 0.9864 | 14000 | 1.5153          | 0.6858   |
| 1.6074        | 1.1273 | 16000 | 1.4965          | 0.6885   |
| 1.5833        | 1.2682 | 18000 | 1.4678          | 0.6934   |
| 1.5649        | 1.4091 | 20000 | 1.4508          | 0.6950   |
| 1.553         | 1.5501 | 22000 | 1.4367          | 0.6985   |
| 1.5345        | 1.6910 | 24000 | 1.4231          | 0.7001   |
| 1.5261        | 1.8319 | 26000 | 1.4157          | 0.7013   |
| 1.5148        | 1.9728 | 28000 | 1.4098          | 0.7027   |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1