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mt5-base-finetuned-english
This model is a fine-tuned version of google/mt5-base on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.3271
- Rouge-1: 31.7
- Rouge-2: 11.83
- Rouge-l: 26.43
- Gen Len: 18.88
- Bertscore: 74.3
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
- 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 |
|---|---|---|---|---|---|---|---|---|
| 4.174 | 1.0 | 3125 | 3.5662 | 27.01 | 7.95 | 22.16 | 18.91 | 72.62 |
| 3.6577 | 2.0 | 6250 | 3.4304 | 28.84 | 9.09 | 23.64 | 18.87 | 73.32 |
| 3.4526 | 3.0 | 9375 | 3.3691 | 29.69 | 9.96 | 24.58 | 18.84 | 73.69 |
| 3.3091 | 4.0 | 12500 | 3.3368 | 30.38 | 10.32 | 25.1 | 18.9 | 73.9 |
| 3.2056 | 5.0 | 15625 | 3.3271 | 30.7 | 10.65 | 25.45 | 18.89 | 73.99 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.0
- Tokenizers 0.12.1
