bart-noised-with-all-dist-2
This model is a fine-tuned version of gayanin/bart-noised-with-all-dist on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3468
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 |
---|---|---|---|
0.5985 | 0.74 | 500 | 0.3934 |
0.3331 | 1.48 | 1000 | 0.3609 |
0.2625 | 2.22 | 1500 | 0.3582 |
0.1968 | 2.96 | 2000 | 0.3468 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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