bart-with-noise-data
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1725
 
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: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 10
 - num_epochs: 3
 - mixed_precision_training: Native AMP
 
Training results
| Training Loss | Epoch | Step | Validation Loss | 
|---|---|---|---|
| 0.34 | 0.87 | 500 | 0.2147 | 
| 0.167 | 1.73 | 1000 | 0.1838 | 
| 0.1393 | 2.6 | 1500 | 0.1725 | 
Framework versions
- Transformers 4.37.2
 - Pytorch 2.1.2+cu121
 - Datasets 2.17.0
 - Tokenizers 0.15.1
 
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Model tree for gayanin/bart-with-noise-data
Base model
facebook/bart-base