longt5-mediasum
This model is a fine-tuned version of google/long-t5-tglobal-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0129
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: 5e-05
- train_batch_size: 12
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.66 | 1.0 | 1667 | 2.0643 |
2.472 | 2.0 | 3334 | 2.0241 |
2.3574 | 3.0 | 5001 | 2.0129 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0a0+17540c5
- Datasets 2.3.2
- Tokenizers 0.12.1
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Model tree for nbroad/longt5-base-global-mediasum
Base model
google/long-t5-tglobal-baseEvaluation results
- ROUGE-1 on xsumtest set verified22.704
- ROUGE-2 on xsumtest set verified5.616
- ROUGE-L on xsumtest set verified18.011
- ROUGE-LSUM on xsumtest set verified18.155
- loss on xsumtest set verified2.166
- gen_len on xsumtest set verified18.353
- ROUGE-1 on cnn_dailymailtest set verified21.152
- ROUGE-2 on cnn_dailymailtest set verified8.132
- ROUGE-L on cnn_dailymailtest set verified16.663
- ROUGE-LSUM on cnn_dailymailtest set verified19.360