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mt5-small_mid_lr_mid_decay
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: 0.7428
- Rouge1: 43.12
- Rouge2: 37.6639
- Rougel: 41.8367
- Rougelsum: 41.904
- Bleu: 31.957
- Gen Len: 12.1285
- Meteor: 0.3936
- No ans accuracy: 22.29
- Av cosine sim: 0.7406
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 9
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len | Meteor | No ans accuracy | Av cosine sim |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3.1455 | 1.0 | 175 | 0.9832 | 18.7107 | 15.4897 | 18.1977 | 18.2212 | 7.0634 | 7.6229 | 0.1626 | 22.4000 | 0.3949 |
| 1.1623 | 1.99 | 350 | 0.8542 | 38.7675 | 32.704 | 37.3557 | 37.3949 | 27.4323 | 12.5135 | 0.3487 | 17.9900 | 0.6992 |
| 0.9431 | 2.99 | 525 | 0.8017 | 41.6216 | 35.6002 | 40.2386 | 40.2881 | 30.7994 | 12.8117 | 0.3755 | 18.37 | 0.7304 |
| 0.8119 | 3.98 | 700 | 0.7787 | 43.5805 | 37.4117 | 42.1059 | 42.155 | 32.9646 | 13.2176 | 0.3947 | 17.7400 | 0.7582 |
| 0.7235 | 4.98 | 875 | 0.7477 | 43.4124 | 37.2017 | 41.8468 | 41.9097 | 32.9345 | 13.116 | 0.3946 | 18.92 | 0.7561 |
| 0.6493 | 5.97 | 1050 | 0.7266 | 40.4764 | 34.9927 | 39.0999 | 39.1711 | 29.0601 | 11.748 | 0.3687 | 22.6500 | 0.7071 |
| 0.5871 | 6.97 | 1225 | 0.7284 | 43.3812 | 37.5544 | 42.0405 | 42.0865 | 32.8345 | 12.6063 | 0.3949 | 21.05 | 0.7485 |
| 0.5453 | 7.96 | 1400 | 0.7389 | 43.4549 | 37.76 | 42.1025 | 42.215 | 32.6726 | 12.4537 | 0.3965 | 21.44 | 0.7496 |
| 0.5038 | 8.96 | 1575 | 0.7428 | 43.12 | 37.6639 | 41.8367 | 41.904 | 31.957 | 12.1285 | 0.3936 | 22.29 | 0.7406 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
