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indic-bert-finetuned-TRAC-DS
This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9922
- Accuracy: 0.5825
- Precision: 0.5493
- Recall: 0.5412
- F1: 0.5428
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: 1e-06
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
---|---|---|---|---|---|---|---|
1.0755 | 1.99 | 612 | 1.0346 | 0.5057 | 0.4072 | 0.4554 | 0.3806 |
1.0175 | 3.99 | 1224 | 1.0096 | 0.5678 | 0.6135 | 0.5011 | 0.4422 |
0.9974 | 5.98 | 1836 | 1.0010 | 0.5776 | 0.5637 | 0.5140 | 0.4799 |
0.9812 | 7.97 | 2448 | 0.9960 | 0.5694 | 0.5426 | 0.5283 | 0.5298 |
0.9675 | 9.97 | 3060 | 0.9956 | 0.5776 | 0.5565 | 0.5422 | 0.5442 |
0.9542 | 11.96 | 3672 | 0.9925 | 0.5882 | 0.5601 | 0.5420 | 0.5419 |
0.944 | 13.95 | 4284 | 0.9907 | 0.5866 | 0.5525 | 0.5441 | 0.5454 |
0.9347 | 15.95 | 4896 | 0.9921 | 0.5858 | 0.5527 | 0.5441 | 0.5456 |
0.9271 | 17.94 | 5508 | 0.9906 | 0.5931 | 0.5596 | 0.5482 | 0.5490 |
0.9236 | 19.93 | 6120 | 0.9922 | 0.5825 | 0.5493 | 0.5412 | 0.5428 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1