---
library_name: transformers
license: apache-2.0
base_model: Sakonii/distilbert-base-nepali
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: BERT_Classifier_DE
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERT_Classifier_DE

This model is a fine-tuned version of [Sakonii/distilbert-base-nepali](https://huggingface.co/Sakonii/distilbert-base-nepali) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8645
- Accuracy: 0.7815
- Recall: 0.6421
- Precision: 0.6362
- F1: 0.6294

## 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: 1.9165942005355648e-05
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch 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: 0.17707559519779958
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 286  | 1.2997          | 0.7902   | 0.25   | 0.1976    | 0.2207 |
| 1.1831        | 2.0   | 572  | 1.0854          | 0.7273   | 0.3508 | 0.2747    | 0.2957 |
| 1.1831        | 3.0   | 858  | 1.0082          | 0.7640   | 0.4274 | 0.4180    | 0.3991 |
| 0.8686        | 4.0   | 1144 | 0.8645          | 0.7815   | 0.6421 | 0.6362    | 0.6294 |
| 0.8686        | 5.0   | 1430 | 0.9993          | 0.7483   | 0.5696 | 0.5609    | 0.5560 |
| 0.6366        | 6.0   | 1716 | 1.1232          | 0.7413   | 0.5868 | 0.4968    | 0.5287 |
| 0.4593        | 7.0   | 2002 | 1.5033          | 0.7483   | 0.4918 | 0.4888    | 0.4902 |
| 0.4593        | 8.0   | 2288 | 1.5870          | 0.7413   | 0.5122 | 0.4819    | 0.4950 |
| 0.3643        | 9.0   | 2574 | 2.0792          | 0.7255   | 0.4719 | 0.4854    | 0.4754 |


### Framework versions

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