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ru_t5_model_for_law_simplification
This model is a fine-tuned version of IlyaGusev/rut5_base_sum_gazeta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Bleu: 0.5066
- Gen Len: 163.03
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: 0.002
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 157 | nan | 0.5066 | 163.03 |
| No log | 2.0 | 314 | nan | 0.5066 | 163.03 |
| No log | 3.0 | 471 | nan | 0.5066 | 163.03 |
| 0.0 | 4.0 | 628 | nan | 0.5066 | 163.03 |
| 0.0 | 5.0 | 785 | nan | 0.5066 | 163.03 |
| 0.0 | 6.0 | 942 | nan | 0.5066 | 163.03 |
| 0.0 | 7.0 | 1099 | nan | 0.5066 | 163.03 |
| 0.0 | 8.0 | 1256 | nan | 0.5066 | 163.03 |
| 0.0 | 9.0 | 1413 | nan | 0.5066 | 163.03 |
| 0.0 | 10.0 | 1570 | nan | 0.5066 | 163.03 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
