metadata
license: apache-2.0
base_model: emilstabil/DanSumT5-baseV_38821V_41166
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: DanSumT5-baseV_38821V_41166V_99300
results: []
DanSumT5-baseV_38821V_41166V_99300
This model is a fine-tuned version of emilstabil/DanSumT5-baseV_38821V_41166 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1990
- Rouge1: 36.0635
- Rouge2: 12.6612
- Rougel: 22.0632
- Rougelsum: 28.8514
- Gen Len: 125.7597
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 232 | 2.1564 | 35.0359 | 12.3281 | 22.0262 | 28.07 | 126.1974 |
No log | 2.0 | 465 | 2.1556 | 35.1832 | 12.0473 | 21.8776 | 28.1858 | 126.4721 |
1.8468 | 3.0 | 697 | 2.1567 | 35.5287 | 12.3174 | 22.3354 | 28.4708 | 126.0987 |
1.8468 | 4.0 | 930 | 2.1524 | 35.5329 | 12.244 | 22.047 | 28.1537 | 126.3863 |
1.7638 | 5.0 | 1162 | 2.1675 | 35.5247 | 12.5574 | 22.5531 | 28.64 | 125.3648 |
1.7638 | 6.0 | 1395 | 2.1637 | 35.4927 | 12.2718 | 22.1521 | 28.5053 | 125.8884 |
1.7082 | 7.0 | 1627 | 2.1771 | 35.7224 | 12.5675 | 22.4379 | 28.6806 | 125.4807 |
1.7082 | 8.0 | 1860 | 2.1809 | 35.4052 | 12.3639 | 22.0898 | 28.0686 | 125.3734 |
1.6599 | 9.0 | 2092 | 2.1828 | 35.3215 | 12.3554 | 22.0962 | 28.1704 | 126.2189 |
1.6599 | 10.0 | 2325 | 2.1852 | 35.2823 | 12.1901 | 21.9675 | 28.1307 | 125.5365 |
1.6125 | 11.0 | 2557 | 2.1903 | 35.198 | 12.051 | 21.901 | 27.819 | 125.3305 |
1.6125 | 12.0 | 2790 | 2.1863 | 35.2787 | 12.0695 | 21.7106 | 28.1589 | 125.6953 |
1.5957 | 13.0 | 3022 | 2.1921 | 35.5594 | 12.4603 | 21.9964 | 28.6257 | 125.97 |
1.5957 | 14.0 | 3255 | 2.2085 | 35.8369 | 12.3539 | 22.0812 | 28.637 | 125.412 |
1.5957 | 15.0 | 3487 | 2.1962 | 35.7638 | 12.5332 | 21.8062 | 28.2834 | 126.3133 |
1.5708 | 16.0 | 3720 | 2.1932 | 35.5401 | 12.3573 | 22.033 | 28.4601 | 125.9614 |
1.5708 | 17.0 | 3952 | 2.1985 | 35.4247 | 12.348 | 21.9465 | 28.2987 | 125.4034 |
1.5644 | 18.0 | 4185 | 2.1987 | 35.4229 | 12.2593 | 21.9969 | 28.2643 | 125.073 |
1.5644 | 19.0 | 4417 | 2.1996 | 35.8265 | 12.5056 | 22.1718 | 28.6138 | 124.9099 |
1.5446 | 19.96 | 4640 | 2.1990 | 36.0635 | 12.6612 | 22.0632 | 28.8514 | 125.7597 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3