mt5-base-finetuned-fa
This model is a fine-tuned version of google/mt5-base on the pn_summary dataset. It achieves the following results on the evaluation set:
- Loss: 2.6477
- Rouge-1: 33.7
- Rouge-2: 21.28
- Rouge-l: 31.69
- Gen Len: 19.0
- Bertscore: 74.52
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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 5
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|---|---|---|---|---|---|---|---|---|
| 3.3828 | 1.0 | 1875 | 2.8114 | 32.17 | 19.47 | 30.12 | 18.99 | 74.25 |
| 2.8204 | 2.0 | 3750 | 2.7080 | 32.67 | 19.92 | 30.56 | 19.0 | 74.31 |
| 2.6907 | 3.0 | 5625 | 2.6724 | 33.22 | 20.44 | 31.11 | 19.0 | 74.47 |
| 2.6029 | 4.0 | 7500 | 2.6513 | 33.46 | 20.75 | 31.38 | 19.0 | 74.54 |
| 2.5414 | 5.0 | 9375 | 2.6477 | 33.68 | 20.91 | 31.62 | 19.0 | 74.58 |
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1