Paraphrase_Muril_onfull
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: 0.3826
- Accuracy: 0.8765
- F1: 0.8764
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.5473 | 1.0 | 157 | 0.5153 | 0.778 | 0.7696 |
0.3562 | 2.0 | 314 | 0.3696 | 0.861 | 0.8610 |
0.2018 | 3.0 | 471 | 0.3483 | 0.8705 | 0.8704 |
0.1973 | 4.0 | 628 | 0.3510 | 0.876 | 0.8760 |
0.1534 | 5.0 | 785 | 0.3826 | 0.8765 | 0.8764 |
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/Paraphrase_Muril_onfull
Base model
google/muril-base-cased