idt5_base-silver-standard
This model is a fine-tuned version of muchad/idt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2726
- Rouge1: 36.3174
- Rouge2: 23.1115
- Rougel: 36.0799
- Rougelsum: 36.0538
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: 0.001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 68.3461 | 1.0 | 149 | 2.9319 | 26.8293 | 15.3216 | 26.1816 | 26.2502 |
| 45.1491 | 2.0 | 298 | 2.4258 | 32.1423 | 19.4385 | 31.7406 | 31.6825 |
| 37.2272 | 3.0 | 447 | 2.2726 | 36.3174 | 23.1115 | 36.0799 | 36.0538 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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Base model
muchad/idt5-base