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t5-small-finetuned-xsum
ParastooC/t5-small-finetuned-xsum
t5-small-finetuned-xsum is a summarization model from ParastooC. 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
- Feb 14, 2023
- Updated
- Feb 28, 2023
- SHA
- b3f3b4b7
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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-xsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2847
- Rouge1: 0.1422
- Rouge2: 0.0403
- Rougel: 0.1337
- Rougelsum: 0.1342
- Gen Len: 8.4248
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7269 | 1.0 | 527 | 1.5826 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5708 | 2.0 | 1054 | 1.4112 | 0.035 | 0.0105 | 0.0357 | 0.0349 | 1.7168 |
| 1.4796 | 3.0 | 1581 | 1.3644 | 0.1012 | 0.0167 | 0.0948 | 0.0942 | 8.2212 |
| 1.3451 | 4.0 | 2108 | 1.3399 | 0.126 | 0.0205 | 0.1183 | 0.1182 | 9.0088 |
| 1.3491 | 5.0 | 2635 | 1.3247 | 0.1307 | 0.0266 | 0.1232 | 0.1236 | 8.0088 |
| 1.3109 | 6.0 | 3162 | 1.3112 | 0.1428 | 0.0325 | 0.1332 | 0.1334 | 7.6549 |
| 1.2462 | 7.0 | 3689 | 1.3046 | 0.1435 | 0.0319 | 0.1342 | 0.1349 | 7.885 |
| 1.2353 | 8.0 | 4216 | 1.2937 | 0.1404 | 0.0313 | 0.1297 | 0.1303 | 9.1239 |
| 1.2838 | 9.0 | 4743 | 1.2903 | 0.1434 | 0.0372 | 0.1338 | 0.1344 | 8.1062 |
| 1.2317 | 10.0 | 5270 | 1.2870 | 0.1459 | 0.0421 | 0.1388 | 0.1389 | 8.4248 |
| 1.2598 | 11.0 | 5797 | 1.2857 | 0.1421 | 0.0403 | 0.1346 | 0.1351 | 8.2389 |
| 1.1579 | 12.0 | 6324 | 1.2847 | 0.1422 | 0.0403 | 0.1337 | 0.1342 | 8.4248 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
- Task
- Summarization
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Feb 14, 2023
- Updated
- Feb 28, 2023