metadata
library_name: transformers
language:
- np
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Nepali-BERT-sentiment
results: []
Nepali-BERT-sentiment
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the Custom Devangari Datasets dataset. It achieves the following results on the evaluation set:
- Loss: 0.6887
- Accuracy: 0.8660
- F1: 0.4658
- Precision: 0.4343
- Recall: 0.5021
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.5999 | 1.0 | 595 | 0.5313 | 0.7274 | 0.3965 | 0.2670 | 0.7700 |
| 0.5114 | 2.0 | 1190 | 0.4717 | 0.7745 | 0.4427 | 0.3106 | 0.7700 |
| 0.4005 | 3.0 | 1785 | 0.4986 | 0.7907 | 0.4556 | 0.3266 | 0.7532 |
| 0.3087 | 4.0 | 2380 | 0.6887 | 0.8660 | 0.4658 | 0.4343 | 0.5021 |
| 0.2292 | 5.0 | 2975 | 0.8148 | 0.8626 | 0.4615 | 0.4240 | 0.5063 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1