flan-t5-large-extraction-cnndm_20000-all
This model is a fine-tuned version of google/flan-t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6652
- Rouge1: 35.487
- Rouge2: 15.6713
- Rougel: 29.9519
- Rougelsum: 29.9368
- Gen Len: 19.0
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: 8
- eval_batch_size: 24
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
2.1295 | 0.08 | 200 | 1.8266 | 34.0465 | 14.7511 | 29.3395 | 29.3437 | 19.0 |
1.9354 | 0.16 | 400 | 1.7732 | 34.7923 | 15.3094 | 29.8484 | 29.8757 | 18.99 |
1.854 | 0.24 | 600 | 1.7367 | 34.8358 | 15.1969 | 29.9971 | 30.0064 | 18.986 |
1.833 | 0.32 | 800 | 1.7120 | 34.7854 | 15.5144 | 29.8141 | 29.7863 | 18.982 |
1.8217 | 0.4 | 1000 | 1.7256 | 34.7274 | 15.2763 | 30.0298 | 30.0871 | 19.0 |
1.8309 | 0.48 | 1200 | 1.7089 | 35.4328 | 15.7724 | 30.0655 | 30.0199 | 19.0 |
1.825 | 0.56 | 1400 | 1.6947 | 35.4116 | 15.6911 | 30.1438 | 30.1764 | 19.0 |
1.7914 | 0.64 | 1600 | 1.7119 | 35.5918 | 16.3762 | 30.3234 | 30.2807 | 19.0 |
1.7889 | 0.72 | 1800 | 1.6810 | 35.6413 | 15.8936 | 30.2848 | 30.2291 | 19.0 |
1.7576 | 0.8 | 2000 | 1.6826 | 35.9424 | 15.6803 | 30.5998 | 30.5571 | 19.0 |
1.7763 | 0.88 | 2200 | 1.6748 | 35.7543 | 15.984 | 30.7197 | 30.721 | 18.998 |
1.7604 | 0.96 | 2400 | 1.6652 | 35.487 | 15.6713 | 29.9519 | 29.9368 | 19.0 |
1.7138 | 1.04 | 2600 | 1.6860 | 36.0333 | 16.4065 | 30.7249 | 30.7168 | 19.0 |
1.6951 | 1.12 | 2800 | 1.6792 | 35.3149 | 15.7178 | 30.1555 | 30.1517 | 18.998 |
1.6752 | 1.2 | 3000 | 1.6832 | 34.7566 | 15.4179 | 29.7687 | 29.8259 | 19.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1
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