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mt5-small-finetuned-28jan-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: 2.5078
- Rouge1: 18.7485
- Rouge2: 5.8034
- Rougel: 18.5163
- Rougelsum: 18.4817
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: 0.0001
- train_batch_size: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
5.9652 | 1.0 | 242 | 2.8048 | 14.036 | 4.037 | 13.7766 | 13.8254 |
3.474 | 2.0 | 484 | 2.7485 | 16.821 | 4.8051 | 16.6168 | 16.5782 |
3.2101 | 3.0 | 726 | 2.6444 | 17.2659 | 5.1077 | 16.9501 | 16.8998 |
3.0555 | 4.0 | 968 | 2.6408 | 17.3002 | 4.8657 | 17.0414 | 16.9794 |
2.9515 | 5.0 | 1210 | 2.5860 | 17.6468 | 5.3816 | 17.3755 | 17.3434 |
2.8694 | 6.0 | 1452 | 2.5586 | 18.3932 | 5.3896 | 18.2521 | 18.0748 |
2.7898 | 7.0 | 1694 | 2.5325 | 18.4954 | 5.5609 | 18.2994 | 18.2112 |
2.7436 | 8.0 | 1936 | 2.5431 | 18.8172 | 5.9338 | 18.4693 | 18.4324 |
2.6955 | 9.0 | 2178 | 2.5588 | 18.7895 | 6.1003 | 18.3593 | 18.3268 |
2.6571 | 10.0 | 2420 | 2.5079 | 19.2525 | 5.8268 | 19.0279 | 18.9846 |
2.629 | 11.0 | 2662 | 2.5118 | 18.9191 | 5.9877 | 18.6505 | 18.6 |
2.5998 | 12.0 | 2904 | 2.5070 | 18.7181 | 5.9061 | 18.4432 | 18.3931 |
2.5692 | 13.0 | 3146 | 2.5014 | 18.4412 | 6.1983 | 18.2394 | 18.1618 |
2.5751 | 14.0 | 3388 | 2.5125 | 18.7014 | 5.9729 | 18.4366 | 18.406 |
2.55 | 15.0 | 3630 | 2.5078 | 18.7485 | 5.8034 | 18.5163 | 18.4817 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2