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DanSumT5-largeV_38143
emilstabil/DanSumT5-largeV_38143
DanSumT5-largeV_38143 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
- b469940e
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-largeV_38143
This model is a fine-tuned version of Danish-summarisation/DanSumT5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9493
- Rouge1: 36.0009
- Rouge2: 12.4957
- Rougel: 22.4757
- Rougelsum: 33.603
- Gen Len: 125.1519
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | 118 | 2.1442 | 34.5887 | 11.0101 | 20.7128 | 32.0179 | 126.1603 |
| No log | 2.0 | 237 | 2.0645 | 34.9243 | 11.2939 | 21.4174 | 32.5111 | 125.7342 |
| No log | 3.0 | 356 | 2.0220 | 35.3258 | 11.7644 | 21.6971 | 32.9952 | 125.3713 |
| No log | 4.0 | 475 | 1.9962 | 35.4098 | 11.883 | 21.6822 | 33.0259 | 124.7553 |
| 2.2257 | 4.99 | 593 | 1.9807 | 36.0239 | 12.4173 | 22.5759 | 33.6794 | 125.038 |
| 2.2257 | 6.0 | 712 | 1.9656 | 35.847 | 12.3976 | 22.3612 | 33.5817 | 125.1646 |
| 2.2257 | 7.0 | 831 | 1.9606 | 35.6499 | 12.1119 | 22.3208 | 33.3221 | 124.6751 |
| 2.2257 | 8.0 | 950 | 1.9533 | 35.6641 | 12.3948 | 22.4477 | 33.3256 | 124.6878 |
| 1.9052 | 8.99 | 1068 | 1.9559 | 35.7509 | 12.4988 | 22.6593 | 33.4865 | 124.4937 |
| 1.9052 | 10.0 | 1187 | 1.9508 | 35.9176 | 12.548 | 22.6092 | 33.6489 | 125.0295 |
| 1.9052 | 10.93 | 1298 | 1.9493 | 36.0009 | 12.4957 | 22.4757 | 33.603 | 125.1519 |
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