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longt5_xl_summ_screen_25
This model is a fine-tuned version of longt5_xl_summ_screen_memsum_20/checkpoint-140 on the learn3r/summ_screen_memsum_oracle dataset. It achieves the following results on the evaluation set:
- Loss: 4.0742
- Rouge1: 39.5624
- Rouge2: 10.2833
- Rougel: 21.2004
- Rougelsum: 34.0767
- Gen Len: 152.0325
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.1846 | 0.97 | 14 | 4.6151 | 37.719 | 9.6532 | 20.2955 | 32.3806 | 100.9527 |
| 0.1441 | 1.95 | 28 | 4.1640 | 36.8632 | 9.6545 | 20.9349 | 31.8954 | 105.5799 |
| 0.1379 | 2.99 | 43 | 4.0742 | 39.5624 | 10.2833 | 21.2004 | 34.0767 | 152.0325 |
| 0.089 | 3.97 | 57 | 4.5216 | 40.2528 | 10.9254 | 21.6978 | 34.6793 | 176.0976 |
| 0.1028 | 4.87 | 70 | 4.1434 | 32.7739 | 9.1305 | 19.6246 | 27.9012 | 59.6775 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
