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DanSumT5-largeV_38143V_15157
emilstabil/DanSumT5-largeV_38143V_15157
DanSumT5-largeV_38143V_15157 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
- Dec 1, 2023
- SHA
- ce2a8bd9
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_38143V_15157
This model is a fine-tuned version of emilstabil/DanSumT5-largeV_38143 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9526
- Rouge1: 36.0906
- Rouge2: 12.3436
- Rougel: 22.6262
- Rougelsum: 33.6191
- Gen Len: 124.7848
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: 3e-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 | 1.9535 | 36.1763 | 12.4392 | 22.5367 | 33.632 | 124.7637 |
| No log | 2.0 | 237 | 1.9579 | 36.074 | 12.4948 | 22.6669 | 33.5774 | 124.2954 |
| No log | 3.0 | 356 | 1.9592 | 35.8935 | 12.4362 | 22.4628 | 33.4068 | 124.3713 |
| No log | 4.0 | 475 | 1.9579 | 35.9893 | 12.4292 | 22.4658 | 33.622 | 124.384 |
| 1.6658 | 4.99 | 593 | 1.9642 | 35.9501 | 12.279 | 22.4227 | 33.4503 | 124.3207 |
| 1.6658 | 6.0 | 712 | 1.9598 | 35.8682 | 12.3408 | 22.5165 | 33.2375 | 124.4135 |
| 1.6658 | 7.0 | 831 | 1.9609 | 35.6712 | 12.0964 | 22.2602 | 33.2817 | 124.8776 |
| 1.6658 | 8.0 | 950 | 1.9567 | 35.8782 | 12.272 | 22.6389 | 33.462 | 124.0084 |
| 1.5814 | 8.99 | 1068 | 1.9591 | 35.888 | 12.278 | 22.4367 | 33.4144 | 124.2658 |
| 1.5814 | 10.0 | 1187 | 1.9544 | 35.8605 | 12.2878 | 22.5468 | 33.4009 | 124.4388 |
| 1.5814 | 10.93 | 1298 | 1.9526 | 36.0906 | 12.3436 | 22.6262 | 33.6191 | 124.7848 |
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
- Dec 1, 2023