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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Sakonii/distilbert-base-nepali |
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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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- recall |
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- precision |
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- f1 |
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model-index: |
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- name: BERT_Classifier_DE |
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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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# BERT_Classifier_DE |
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This model is a fine-tuned version of [Sakonii/distilbert-base-nepali](https://huggingface.co/Sakonii/distilbert-base-nepali) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8645 |
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- Accuracy: 0.7815 |
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- Recall: 0.6421 |
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- Precision: 0.6362 |
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- F1: 0.6294 |
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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: 1.9165942005355648e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.17707559519779958 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 286 | 1.2997 | 0.7902 | 0.25 | 0.1976 | 0.2207 | |
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| 1.1831 | 2.0 | 572 | 1.0854 | 0.7273 | 0.3508 | 0.2747 | 0.2957 | |
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| 1.1831 | 3.0 | 858 | 1.0082 | 0.7640 | 0.4274 | 0.4180 | 0.3991 | |
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| 0.8686 | 4.0 | 1144 | 0.8645 | 0.7815 | 0.6421 | 0.6362 | 0.6294 | |
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| 0.8686 | 5.0 | 1430 | 0.9993 | 0.7483 | 0.5696 | 0.5609 | 0.5560 | |
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| 0.6366 | 6.0 | 1716 | 1.1232 | 0.7413 | 0.5868 | 0.4968 | 0.5287 | |
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| 0.4593 | 7.0 | 2002 | 1.5033 | 0.7483 | 0.4918 | 0.4888 | 0.4902 | |
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| 0.4593 | 8.0 | 2288 | 1.5870 | 0.7413 | 0.5122 | 0.4819 | 0.4950 | |
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| 0.3643 | 9.0 | 2574 | 2.0792 | 0.7255 | 0.4719 | 0.4854 | 0.4754 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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