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t5-small-finetuned-giga
MJS2022/t5-small-finetuned-giga
t5-small-finetuned-giga is a machine learning model from MJS2022. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Dec 1, 2022
- Updated
- Dec 1, 2022
- SHA
- d7ae77f4
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
t5-small-finetuned-giga
This model is a fine-tuned version of t5-small on the gigaword dataset. It achieves the following results on the evaluation set:
- Loss: 3.2594
- Rouge1: 26.6579
- Rouge2: 9.5505
- Rougel: 24.4987
- Rougelsum: 24.5146
- Gen Len: 13.5436
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.8512 | 1.0 | 23775 | 3.2594 | 26.6579 | 9.5505 | 24.4987 | 24.5146 | 13.5436 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 1, 2022
- Updated
- Dec 1, 2022