mt5-small-clara-med
This model is a fine-tuned version of google/mt5-small on the CLARA-MeD dataset. It achieves the following results on the evaluation set:
- Loss: 1.9850
- Rouge1: 33.0363
- Rouge2: 19.0613
- Rougel: 30.295
- Rougelsum: 30.2898
- SARI: 40.7094
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 190 | 3.0286 | 18.0709 | 7.727 | 16.1995 | 16.3348 |
| No log | 2.0 | 380 | 2.4754 | 24.9167 | 13.0501 | 22.3889 | 22.4724 |
| 6.79 | 3.0 | 570 | 2.3542 | 29.9908 | 15.9829 | 26.3751 | 26.4343 |
| 6.79 | 4.0 | 760 | 2.2894 | 30.4435 | 16.3176 | 27.1801 | 27.1926 |
| 3.1288 | 5.0 | 950 | 2.2440 | 30.8602 | 16.8033 | 27.8195 | 27.8355 |
| 3.1288 | 6.0 | 1140 | 2.1772 | 31.4202 | 17.3253 | 28.3394 | 28.3699 |
| 3.1288 | 7.0 | 1330 | 2.1584 | 31.5591 | 17.7302 | 28.618 | 28.6189 |
| 2.7919 | 8.0 | 1520 | 2.1286 | 31.6211 | 17.7423 | 28.7218 | 28.7462 |
| 2.7919 | 9.0 | 1710 | 2.1031 | 31.9724 | 18.017 | 29.0754 | 29.0744 |
| 2.6007 | 10.0 | 1900 | 2.0947 | 32.1588 | 18.2474 | 29.2957 | 29.2956 |
| 2.6007 | 11.0 | 2090 | 2.0914 | 32.4959 | 18.4197 | 29.6052 | 29.609 |
| 2.6007 | 12.0 | 2280 | 2.0726 | 32.6673 | 18.8962 | 29.9145 | 29.9122 |
| 2.4911 | 13.0 | 2470 | 2.0487 | 32.4461 | 18.6804 | 29.6224 | 29.6274 |
| 2.4911 | 14.0 | 2660 | 2.0436 | 32.8393 | 19.0315 | 30.1024 | 30.1097 |
| 2.4168 | 15.0 | 2850 | 2.0229 | 32.8235 | 18.9549 | 30.0699 | 30.0605 |
| 2.4168 | 16.0 | 3040 | 2.0253 | 32.8584 | 18.8602 | 30.0582 | 30.0712 |
| 2.4168 | 17.0 | 3230 | 2.0177 | 32.7145 | 18.9059 | 30.0436 | 30.0771 |
| 2.3452 | 18.0 | 3420 | 2.0151 | 32.6874 | 18.8339 | 29.9739 | 30.0004 |
| 2.3452 | 19.0 | 3610 | 2.0138 | 32.516 | 18.6562 | 29.7823 | 29.7951 |
| 2.302 | 20.0 | 3800 | 2.0085 | 32.8117 | 18.8208 | 30.0902 | 30.1282 |
| 2.302 | 21.0 | 3990 | 2.0043 | 32.7633 | 18.8364 | 30.0619 | 30.0781 |
| 2.302 | 22.0 | 4180 | 1.9972 | 32.9786 | 19.0354 | 30.2166 | 30.2286 |
| 2.2641 | 23.0 | 4370 | 1.9927 | 33.0222 | 19.0501 | 30.2716 | 30.2951 |
| 2.2641 | 24.0 | 4560 | 1.9905 | 32.9557 | 18.9958 | 30.1988 | 30.2004 |
| 2.2366 | 25.0 | 4750 | 1.9897 | 33.0429 | 18.9806 | 30.2861 | 30.3012 |
| 2.2366 | 26.0 | 4940 | 1.9850 | 33.047 | 19.118 | 30.3437 | 30.3368 |
| 2.2366 | 27.0 | 5130 | 1.9860 | 33.0736 | 19.0805 | 30.3311 | 30.3476 |
| 2.2157 | 28.0 | 5320 | 1.9870 | 33.0698 | 19.0649 | 30.2959 | 30.3093 |
| 2.2157 | 29.0 | 5510 | 1.9844 | 33.0376 | 19.0397 | 30.299 | 30.2839 |
| 2.2131 | 30.0 | 5700 | 1.9850 | 33.0363 | 19.0613 | 30.295 | 30.2898 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1
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