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summarize_t5-small_billsum_finetune
jonastokoliu/summarize_t5-small_billsum_finetune
summarize_t5-small_billsum_finetune is a machine learning model from jonastokoliu. 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
- May 27, 2023
- Updated
- May 27, 2023
- SHA
- 0b4c7d3d
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. -->
summarize_t5-small_billsum_finetune
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.0625
- Rouge1: 0.1317
- Rouge2: 0.0435
- Rougel: 0.1125
- Rougelsum: 0.1127
- Gen Len: 20.0
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 31 | 3.2722 | 0.1362 | 0.0466 | 0.1158 | 0.116 | 20.0 |
| No log | 2.0 | 62 | 3.0625 | 0.1317 | 0.0435 | 0.1125 | 0.1127 | 20.0 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- May 27, 2023
- Updated
- May 27, 2023