MahaPhrase_mahaBERTv2_Finetuning
This model is a fine-tuned version of l3cube-pune/marathi-bert-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1024
- Accuracy: 0.976
- F1: 0.9758
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: 2.8310088601700302e-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 |
---|---|---|---|---|---|
0.5141 | 1.0 | 71 | 0.5038 | 0.892 | 0.8920 |
0.3341 | 2.0 | 142 | 0.3101 | 0.96 | 0.9596 |
0.222 | 3.0 | 213 | 0.1985 | 0.968 | 0.9676 |
0.14 | 4.0 | 284 | 0.1937 | 0.948 | 0.9468 |
0.078 | 5.0 | 355 | 0.1660 | 0.956 | 0.9551 |
0.0716 | 6.0 | 426 | 0.1024 | 0.976 | 0.9758 |
0.0505 | 7.0 | 497 | 0.1560 | 0.964 | 0.9633 |
0.0366 | 8.0 | 568 | 0.1057 | 0.976 | 0.9757 |
0.0232 | 9.0 | 639 | 0.0895 | 0.976 | 0.9757 |
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_mahaBERTv2_Finetuning
Base model
l3cube-pune/marathi-bert-v2