Paraphrase_Muril_onfull_FT2
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: 0.3748
 - Accuracy: 0.869
 - F1: 0.8690
 
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: 1.57262772498186e-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 | 
|---|---|---|---|---|---|
| 0.5558 | 1.0 | 157 | 0.5337 | 0.847 | 0.8457 | 
| 0.4157 | 2.0 | 314 | 0.4331 | 0.8645 | 0.8643 | 
| 0.3366 | 3.0 | 471 | 0.3985 | 0.859 | 0.8590 | 
| 0.2919 | 4.0 | 628 | 0.3822 | 0.863 | 0.8629 | 
| 0.2527 | 5.0 | 785 | 0.3748 | 0.869 | 0.8690 | 
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_FT2
Base model
google/muril-base-cased