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t5-base-samsum
antonkurylo/t5-base-samsum
t5-base-samsum is a summarization model from antonkurylo. Use it when you need a shorter version of a longer text. 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
- Task
- Summarization
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- May 22, 2023
- Updated
- May 22, 2023
- SHA
- e329cf84
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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-base-samsum
This model is a fine-tuned version of t5-base on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 0.6172
- Rouge1: 48.9131
- Rouge2: 25.4942
- Rougel: 41.2363
- Rougelsum: 45.3434
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.7606 | 1.0 | 3683 | 0.6254 | 46.9778 | 23.8245 | 39.8294 | 43.4639 |
| 0.6273 | 2.0 | 7366 | 0.6119 | 48.2515 | 24.7534 | 40.4415 | 44.5567 |
| 0.5769 | 3.0 | 11049 | 0.6116 | 48.228 | 24.7865 | 40.7537 | 44.4026 |
| 0.5412 | 4.0 | 14732 | 0.6145 | 48.8563 | 25.356 | 41.1913 | 45.186 |
| 0.5199 | 5.0 | 18415 | 0.6172 | 48.9131 | 25.4942 | 41.2363 | 45.3434 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Summarization
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- May 22, 2023
- Updated
- May 22, 2023