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DanSumT5-smallV_45767
emilstabil/DanSumT5-smallV_45767
DanSumT5-smallV_45767 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 30, 2023
- Updated
- Nov 30, 2023
- SHA
- ed7835f3
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_45767
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: 2.4588
- Rouge1: 34.0971
- Rouge2: 11.6678
- Rougel: 20.9389
- Rougelsum: 31.6394
- Gen Len: 126.6667
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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- 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 | 0.99 | 47 | 2.6271 | 33.2283 | 9.8941 | 19.1924 | 30.4729 | 126.1097 |
| No log | 2.0 | 95 | 2.5692 | 34.2858 | 10.6816 | 20.0299 | 31.4449 | 126.3122 |
| No log | 2.99 | 142 | 2.5355 | 33.7958 | 10.5765 | 20.2505 | 31.1959 | 126.3797 |
| No log | 4.0 | 190 | 2.5069 | 33.9743 | 10.8243 | 20.5625 | 31.5943 | 127.0 |
| No log | 4.99 | 237 | 2.4948 | 34.3448 | 11.0631 | 20.7157 | 31.8031 | 126.8143 |
| No log | 6.0 | 285 | 2.4850 | 34.3003 | 11.2431 | 20.8124 | 31.6921 | 126.7722 |
| No log | 6.99 | 332 | 2.4732 | 34.4809 | 11.2159 | 20.887 | 31.8901 | 126.4641 |
| No log | 8.0 | 380 | 2.4653 | 34.4969 | 11.2692 | 20.9618 | 31.9055 | 126.8312 |
| No log | 8.99 | 427 | 2.4620 | 34.103 | 11.3392 | 20.7891 | 31.5918 | 126.6709 |
| No log | 10.0 | 475 | 2.4598 | 34.3248 | 11.7302 | 21.0723 | 31.8667 | 126.6878 |
| 2.7898 | 10.88 | 517 | 2.4588 | 34.0971 | 11.6678 | 20.9389 | 31.6394 | 126.6667 |
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 30, 2023
- Updated
- Nov 30, 2023