metadata
license: cc-by-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: l3cube-pune/hing-roberta
model-index:
- name: hing-roberta-NCM-run-2
results: []
hing-roberta-NCM-run-2
This model is a fine-tuned version of l3cube-pune/hing-roberta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3647
- Accuracy: 0.6483
- Precision: 0.6369
- Recall: 0.6325
- F1: 0.6341
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 |
|---|---|---|---|---|---|---|---|
| 0.8973 | 1.0 | 927 | 0.8166 | 0.6483 | 0.6545 | 0.6576 | 0.6460 |
| 0.6827 | 2.0 | 1854 | 0.9071 | 0.6526 | 0.6444 | 0.6261 | 0.6299 |
| 0.4672 | 3.0 | 2781 | 1.1600 | 0.6764 | 0.6657 | 0.6634 | 0.6643 |
| 0.3388 | 4.0 | 3708 | 1.7426 | 0.6548 | 0.6406 | 0.6442 | 0.6418 |
| 0.2786 | 5.0 | 4635 | 1.9385 | 0.6505 | 0.6484 | 0.6437 | 0.6434 |
| 0.1794 | 6.0 | 5562 | 2.3158 | 0.6472 | 0.6564 | 0.6365 | 0.6388 |
| 0.12 | 7.0 | 6489 | 2.6961 | 0.6591 | 0.6458 | 0.6531 | 0.6466 |
| 0.1298 | 8.0 | 7416 | 2.7196 | 0.6505 | 0.6523 | 0.6307 | 0.6342 |
| 0.0941 | 9.0 | 8343 | 2.5853 | 0.6548 | 0.6406 | 0.6426 | 0.6415 |
| 0.0696 | 10.0 | 9270 | 2.8386 | 0.6613 | 0.6616 | 0.6314 | 0.6348 |
| 0.0722 | 11.0 | 10197 | 2.9658 | 0.6537 | 0.6356 | 0.6356 | 0.6355 |
| 0.0509 | 12.0 | 11124 | 3.3286 | 0.6429 | 0.6262 | 0.6192 | 0.6214 |
| 0.0444 | 13.0 | 12051 | 3.1654 | 0.6483 | 0.6347 | 0.6302 | 0.6319 |
| 0.0341 | 14.0 | 12978 | 2.9509 | 0.6537 | 0.6430 | 0.6394 | 0.6401 |
| 0.0345 | 15.0 | 13905 | 3.3416 | 0.6656 | 0.6514 | 0.6488 | 0.6499 |
| 0.0303 | 16.0 | 14832 | 3.3874 | 0.6419 | 0.6267 | 0.6339 | 0.6272 |
| 0.0245 | 17.0 | 15759 | 3.2854 | 0.6570 | 0.6428 | 0.6420 | 0.6421 |
| 0.0174 | 18.0 | 16686 | 3.2863 | 0.6602 | 0.6569 | 0.6427 | 0.6465 |
| 0.0136 | 19.0 | 17613 | 3.3674 | 0.6494 | 0.6361 | 0.6341 | 0.6349 |
| 0.0111 | 20.0 | 18540 | 3.3647 | 0.6483 | 0.6369 | 0.6325 | 0.6341 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1