| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: indic-bert-finetuned-non-code-mixed-DS |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # indic-bert-finetuned-non-code-mixed-DS |
|
|
| This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9997 |
| - Accuracy: 0.5620 |
| - Precision: 0.5591 |
| - Recall: 0.5203 |
| - F1: 0.5078 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-06 |
| - train_batch_size: 32 |
| - eval_batch_size: 16 |
| - seed: 43 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 1.0673 | 3.99 | 926 | 1.0361 | 0.4142 | 0.4092 | 0.3851 | 0.2750 | |
| | 1.0144 | 7.98 | 1852 | 1.0147 | 0.5146 | 0.5851 | 0.4714 | 0.4184 | |
| | 0.9882 | 11.97 | 2778 | 1.0045 | 0.5599 | 0.5728 | 0.5191 | 0.5047 | |
| | 0.9699 | 15.97 | 3704 | 1.0004 | 0.5642 | 0.5620 | 0.5264 | 0.5193 | |
| | 0.9591 | 19.96 | 4630 | 0.9997 | 0.5620 | 0.5591 | 0.5203 | 0.5078 | |
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| ### Framework versions |
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|
| - Transformers 4.20.1 |
| - Pytorch 1.10.1+cu111 |
| - Datasets 2.3.2 |
| - Tokenizers 0.12.1 |
|
|
