---
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: nepali-grammar-20250215_1722
  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. -->

# nepali-grammar-20250215_1722

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: 0.2446
- Accuracy: 0.9093
- F1: 0.9171
- Precision: 0.9510
- Recall: 0.8856

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.25          | 1.0    | 14063 | 0.2447          | 0.9036   | 0.9113 | 0.9524    | 0.8736 |
| 0.2106        | 2.0    | 28126 | 0.2375          | 0.9088   | 0.9167 | 0.9497    | 0.8859 |
| 0.1811        | 2.9998 | 42186 | 0.2446          | 0.9093   | 0.9171 | 0.9510    | 0.8856 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0