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mt5-small-finetuned-18jan-2
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6070
- Rouge1: 5.8815
- Rouge2: 0.3333
- Rougel: 5.8065
- Rougelsum: 5.7756
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: 0.0002
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 7.6303 | 1.0 | 60 | 3.0842 | 5.9419 | 0.9768 | 6.0316 | 6.0505 |
| 3.8899 | 2.0 | 120 | 2.7540 | 7.8799 | 0.5667 | 7.9069 | 7.8884 |
| 3.4335 | 3.0 | 180 | 2.7391 | 8.4788 | 0.5667 | 8.4352 | 8.4595 |
| 3.2524 | 4.0 | 240 | 2.6775 | 8.6704 | 0.4167 | 8.6495 | 8.6537 |
| 3.0853 | 5.0 | 300 | 2.6776 | 7.8484 | 0.1667 | 7.7371 | 7.7464 |
| 2.974 | 6.0 | 360 | 2.6641 | 8.4292 | 0.1667 | 8.2708 | 8.35 |
| 2.9018 | 7.0 | 420 | 2.6233 | 7.1548 | 0.3333 | 7.1393 | 7.1179 |
| 2.859 | 8.0 | 480 | 2.6238 | 6.6333 | 0.4167 | 6.597 | 6.5845 |
| 2.8123 | 9.0 | 540 | 2.5961 | 6.4519 | 0.3333 | 6.3113 | 6.3519 |
| 2.7843 | 10.0 | 600 | 2.6070 | 5.8815 | 0.3333 | 5.8065 | 5.7756 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
