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--- |
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library_name: transformers |
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license: cc-by-4.0 |
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base_model: l3cube-pune/indic-sentence-bert-nli |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: indic-sentence-bert-nli-profanity-mr |
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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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# indic-sentence-bert-nli-profanity-mr |
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This model is a fine-tuned version of [l3cube-pune/indic-sentence-bert-nli](https://huggingface.co/l3cube-pune/indic-sentence-bert-nli) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4716 |
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- Accuracy: 0.9035 |
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- Precision: 0.4517 |
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- Recall: 0.5 |
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- F1: 0.4746 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.5063 | 0.9836 | 30 | 0.4867 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.3827 | 2.0 | 61 | 0.3841 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.331 | 2.9836 | 91 | 0.3633 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.323 | 4.0 | 122 | 0.3648 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.295 | 4.9836 | 152 | 0.3657 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.3048 | 6.0 | 183 | 0.3668 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.3168 | 6.9836 | 213 | 0.3667 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.3112 | 8.0 | 244 | 0.3666 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.2971 | 8.9836 | 274 | 0.3663 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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| 0.3009 | 9.8361 | 300 | 0.3662 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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