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--- |
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library_name: transformers |
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language: |
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- np |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: Nepali-BERT-sentiment |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Nepali-BERT-sentiment |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the Custom Devangari Datasets dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6887 |
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- Accuracy: 0.8660 |
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- F1: 0.4658 |
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- Precision: 0.4343 |
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- Recall: 0.5021 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.5999 | 1.0 | 595 | 0.5313 | 0.7274 | 0.3965 | 0.2670 | 0.7700 | |
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| 0.5114 | 2.0 | 1190 | 0.4717 | 0.7745 | 0.4427 | 0.3106 | 0.7700 | |
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| 0.4005 | 3.0 | 1785 | 0.4986 | 0.7907 | 0.4556 | 0.3266 | 0.7532 | |
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| 0.3087 | 4.0 | 2380 | 0.6887 | 0.8660 | 0.4658 | 0.4343 | 0.5021 | |
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| 0.2292 | 5.0 | 2975 | 0.8148 | 0.8626 | 0.4615 | 0.4240 | 0.5063 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
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