<!-- 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-combined-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: 0.9783
- Accuracy: 0.5871
- Precision: 0.5527
- Recall: 0.5574
- F1: 0.5537
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: 16
- 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 |
|---|---|---|---|---|---|---|---|
| 1.0904 | 1.0 | 711 | 1.0759 | 0.4452 | 0.4368 | 0.4155 | 0.3333 |
| 1.0537 | 2.0 | 1422 | 1.0363 | 0.5063 | 0.5079 | 0.4902 | 0.4889 |
| 1.0233 | 3.0 | 2133 | 1.0207 | 0.5302 | 0.5195 | 0.5266 | 0.4956 |
| 1.0091 | 3.99 | 2844 | 1.0168 | 0.5379 | 0.5248 | 0.5313 | 0.5124 |
| 0.9983 | 4.99 | 3555 | 1.0009 | 0.5681 | 0.5344 | 0.5424 | 0.5335 |
| 0.9854 | 5.99 | 4266 | 0.9950 | 0.5829 | 0.5490 | 0.5548 | 0.5492 |
| 0.9728 | 6.99 | 4977 | 0.9917 | 0.5751 | 0.5436 | 0.5515 | 0.5434 |
| 0.9616 | 7.99 | 5688 | 0.9888 | 0.5492 | 0.5183 | 0.5308 | 0.5107 |
| 0.9476 | 8.99 | 6399 | 0.9815 | 0.5836 | 0.5488 | 0.5526 | 0.5499 |
| 0.9355 | 9.99 | 7110 | 0.9962 | 0.5520 | 0.5316 | 0.5419 | 0.5223 |
| 0.924 | 10.98 | 7821 | 0.9823 | 0.5674 | 0.5363 | 0.5453 | 0.5315 |
| 0.9112 | 11.98 | 8532 | 0.9773 | 0.5829 | 0.5479 | 0.5504 | 0.5488 |
| 0.9002 | 12.98 | 9243 | 0.9761 | 0.5815 | 0.5452 | 0.5479 | 0.5459 |
| 0.8904 | 13.98 | 9954 | 0.9726 | 0.5913 | 0.5558 | 0.5495 | 0.5512 |
| 0.8823 | 14.98 | 10665 | 0.9785 | 0.5843 | 0.5526 | 0.5583 | 0.5533 |
| 0.8742 | 15.98 | 11376 | 0.9765 | 0.5843 | 0.5493 | 0.5543 | 0.5500 |
| 0.8653 | 16.98 | 12087 | 0.9746 | 0.5864 | 0.5501 | 0.5532 | 0.5508 |
| 0.8612 | 17.97 | 12798 | 0.9770 | 0.5885 | 0.5539 | 0.5566 | 0.5548 |
| 0.8558 | 18.97 | 13509 | 0.9796 | 0.5836 | 0.5510 | 0.5565 | 0.5520 |
| 0.8561 | 19.97 | 14220 | 0.9783 | 0.5871 | 0.5527 | 0.5574 | 0.5537 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
