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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: google/muril-base-cased
model-index:
- name: nepali_complaints_classification_muril3
  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_complaints_classification_muril3

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: 0.2575

## 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
- lr_scheduler_warmup_steps: 50
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3973        | 0.25  | 500  | 2.0247          |
| 1.7073        | 0.5   | 1000 | 1.3814          |
| 1.1586        | 0.75  | 1500 | 0.9054          |
| 0.8099        | 1.0   | 2000 | 0.6431          |
| 0.5456        | 1.25  | 2500 | 0.4845          |
| 0.434         | 1.5   | 3000 | 0.4157          |
| 0.3643        | 1.75  | 3500 | 0.3814          |
| 0.3144        | 2.01  | 4000 | 0.3432          |
| 0.2616        | 2.26  | 4500 | 0.3156          |
| 0.2418        | 2.51  | 5000 | 0.2952          |
| 0.2256        | 2.76  | 5500 | 0.2805          |
| 0.2157        | 3.01  | 6000 | 0.2908          |
| 0.1749        | 3.26  | 6500 | 0.2847          |
| 0.1626        | 3.51  | 7000 | 0.2734          |
| 0.1522        | 3.76  | 7500 | 0.2658          |
| 0.1443        | 4.01  | 8000 | 0.2560          |
| 0.1196        | 4.26  | 8500 | 0.2580          |
| 0.1138        | 4.51  | 9000 | 0.2618          |
| 0.1119        | 4.76  | 9500 | 0.2575          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2