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DanSumT5-smallV_55565
emilstabil/DanSumT5-smallV_55565
DanSumT5-smallV_55565 is a machine learning model from emilstabil. 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
- mt5
- Access
- Public
- Created
- Nov 29, 2023
- Updated
- Nov 29, 2023
- SHA
- a12ff5ee
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. -->
DanSumT5-smallV_55565
This model is a fine-tuned version of Danish-summarisation/DanSumT5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6152
- Rouge1: 33.2076
- Rouge2: 9.7687
- Rougel: 19.2885
- Rougelsum: 30.5358
- Gen Len: 125.4515
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: 80
- eval_batch_size: 80
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 320
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 6 | 2.7915 | 28.1925 | 6.0798 | 16.0171 | 25.4406 | 117.8734 |
| No log | 2.0 | 12 | 2.7309 | 30.7001 | 7.8441 | 17.6277 | 28.1658 | 123.7384 |
| No log | 3.0 | 18 | 2.6932 | 31.9139 | 8.8623 | 18.4491 | 29.2043 | 125.2321 |
| No log | 4.0 | 24 | 2.6673 | 32.1541 | 9.2757 | 18.7349 | 29.3827 | 125.1941 |
| No log | 5.0 | 30 | 2.6506 | 32.6317 | 9.6369 | 18.9798 | 30.0012 | 125.6034 |
| No log | 6.0 | 36 | 2.6391 | 32.7076 | 9.7264 | 18.9488 | 29.9797 | 125.3376 |
| No log | 7.0 | 42 | 2.6307 | 32.9958 | 9.8324 | 19.0395 | 30.2766 | 125.0 |
| No log | 8.0 | 48 | 2.6241 | 33.2035 | 9.9866 | 19.1625 | 30.5136 | 125.2321 |
| No log | 9.0 | 54 | 2.6190 | 33.4626 | 10.076 | 19.2999 | 30.6955 | 125.4515 |
| No log | 10.0 | 60 | 2.6161 | 33.3145 | 9.9106 | 19.3186 | 30.6521 | 125.4515 |
| No log | 11.0 | 66 | 2.6152 | 33.2076 | 9.7687 | 19.2885 | 30.5358 | 125.4515 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1+git7548e2f
- Datasets 2.13.2
- Tokenizers 0.13.3
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Nov 29, 2023
- Updated
- Nov 29, 2023