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mt5-small-finetuned-QMSum-01
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8022
- Rouge1: 18.0578
- Rouge2: 4.3867
- Rougel: 14.448
- Rougelsum: 16.1248
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: 5.6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 5.8153 | 1.0 | 548 | 3.0610 | 11.8231 | 3.1478 | 9.9085 | 10.7642 |
| 3.5393 | 2.0 | 1096 | 2.9173 | 16.1634 | 4.0585 | 13.0541 | 14.6676 |
| 3.2879 | 3.0 | 1644 | 2.8507 | 16.6082 | 4.1563 | 13.4818 | 14.9447 |
| 3.163 | 4.0 | 2192 | 2.8268 | 16.9681 | 4.1602 | 13.7462 | 15.0741 |
| 3.0699 | 5.0 | 2740 | 2.8256 | 17.8647 | 4.5317 | 14.4077 | 15.8516 |
| 3.0156 | 6.0 | 3288 | 2.8175 | 17.7178 | 4.3329 | 14.3377 | 15.8622 |
| 2.9692 | 7.0 | 3836 | 2.7987 | 18.3523 | 4.6726 | 14.6873 | 16.413 |
| 2.9531 | 8.0 | 4384 | 2.8022 | 18.0578 | 4.3867 | 14.448 | 16.1248 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
