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flan-t5-base-extraction-cnndm_20000-all-hint_precision-ep50
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6865
- Hint Hit Num: 2.3572
- Hint Precision: 0.4273
- Num: 5.5014
- Gen Len: 18.9996
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: 2e-05
- train_batch_size: 60
- eval_batch_size: 400
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Hint Hit Num | Hint Precision | Num | Gen Len |
|---|---|---|---|---|---|---|---|
| 2.1368 | 1.2 | 400 | 1.7751 | 2.203 | 0.4143 | 5.3192 | 18.9994 |
| 1.9563 | 2.4 | 800 | 1.7394 | 2.2359 | 0.4182 | 5.3459 | 18.9999 |
| 1.8966 | 3.59 | 1200 | 1.7167 | 2.2493 | 0.4172 | 5.3808 | 19.0 |
| 1.8669 | 4.79 | 1600 | 1.6975 | 2.2785 | 0.4208 | 5.4041 | 18.9999 |
| 1.8311 | 5.99 | 2000 | 1.6944 | 2.2849 | 0.4202 | 5.4243 | 18.9999 |
| 1.8044 | 7.19 | 2400 | 1.6918 | 2.2822 | 0.4214 | 5.4014 | 18.9998 |
| 1.7837 | 8.38 | 2800 | 1.6875 | 2.3155 | 0.425 | 5.4314 | 18.9999 |
| 1.7622 | 9.58 | 3200 | 1.6832 | 2.3069 | 0.423 | 5.4366 | 18.9996 |
| 1.7424 | 10.78 | 3600 | 1.6861 | 2.3173 | 0.4246 | 5.4455 | 18.9999 |
| 1.7318 | 11.98 | 4000 | 1.6856 | 2.3389 | 0.4246 | 5.4939 | 18.9999 |
| 1.7084 | 13.17 | 4400 | 1.6865 | 2.3572 | 0.4273 | 5.5014 | 18.9996 |
| 1.6946 | 14.37 | 4800 | 1.6817 | 2.3177 | 0.4219 | 5.4749 | 18.9996 |
| 1.685 | 15.57 | 5200 | 1.6884 | 2.3499 | 0.4262 | 5.4982 | 18.9999 |
| 1.6686 | 16.77 | 5600 | 1.6879 | 2.3466 | 0.4242 | 5.5094 | 18.9995 |
| 1.6583 | 17.96 | 6000 | 1.6885 | 2.3547 | 0.4255 | 5.5123 | 18.9993 |
| 1.6462 | 19.16 | 6400 | 1.6874 | 2.3582 | 0.4259 | 5.5165 | 18.9993 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1
