MahaPhrase_Muril_finetuning
This model is a fine-tuned version of google/muril-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1347
- Accuracy: 0.968
- F1: 0.9678
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: 4.845270580652351e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 9
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.4855 | 1.0 | 71 | 0.4922 | 0.864 | 0.8640 |
0.2816 | 2.0 | 142 | 0.2540 | 0.94 | 0.9395 |
0.2294 | 3.0 | 213 | 0.1347 | 0.968 | 0.9678 |
0.0831 | 4.0 | 284 | 0.1278 | 0.964 | 0.9634 |
0.0341 | 5.0 | 355 | 0.1256 | 0.964 | 0.9636 |
0.0675 | 6.0 | 426 | 0.1411 | 0.968 | 0.9675 |
0.0224 | 7.0 | 497 | 0.1532 | 0.964 | 0.9634 |
0.0064 | 8.0 | 568 | 0.1388 | 0.968 | 0.9675 |
0.0211 | 9.0 | 639 | 0.1504 | 0.968 | 0.9675 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for Abhi964/MahaPhrase_Muril_finetuning
Base model
google/muril-base-cased