metadata
license: apache-2.0
base_model: emilstabil/DanSumT5-baseV_38821
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: DanSumT5-baseV_38821V_41166
results: []
DanSumT5-baseV_38821V_41166
This model is a fine-tuned version of emilstabil/DanSumT5-baseV_38821 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1413
- Rouge1: 35.0654
- Rouge2: 11.6563
- Rougel: 21.7686
- Rougelsum: 27.7516
- Gen Len: 126.3262
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: 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 | 2.1957 | 34.7339 | 11.6712 | 21.4644 | 27.6817 | 126.4592 |
| No log | 2.0 | 465 | 2.1830 | 34.8759 | 12.139 | 21.5278 | 27.3465 | 126.4549 |
| 2.2462 | 3.0 | 697 | 2.1705 | 35.3017 | 12.4909 | 21.9387 | 28.2423 | 126.4807 |
| 2.2462 | 4.0 | 930 | 2.1654 | 34.8508 | 11.4696 | 21.4196 | 27.6267 | 126.279 |
| 2.1581 | 5.0 | 1162 | 2.1613 | 35.223 | 12.1452 | 21.8105 | 28.3086 | 126.6094 |
| 2.1581 | 6.0 | 1395 | 2.1515 | 35.5785 | 12.0532 | 21.9575 | 28.5902 | 126.7082 |
| 2.0992 | 7.0 | 1627 | 2.1560 | 35.1162 | 11.7299 | 21.6834 | 28.0683 | 126.3562 |
| 2.0992 | 8.0 | 1860 | 2.1519 | 35.286 | 11.9648 | 21.8717 | 28.0591 | 126.5193 |
| 2.0477 | 9.0 | 2092 | 2.1471 | 34.9886 | 11.763 | 21.5827 | 27.9164 | 126.5622 |
| 2.0477 | 10.0 | 2325 | 2.1454 | 35.23 | 11.9011 | 21.891 | 28.0888 | 126.2403 |
| 1.9999 | 11.0 | 2557 | 2.1462 | 35.2311 | 12.1353 | 22.1785 | 28.2209 | 126.1803 |
| 1.9999 | 12.0 | 2790 | 2.1411 | 35.0426 | 11.81 | 21.9802 | 28.0833 | 126.515 |
| 1.9791 | 13.0 | 3022 | 2.1417 | 34.8836 | 11.419 | 21.6238 | 27.6304 | 126.6738 |
| 1.9791 | 14.0 | 3255 | 2.1459 | 35.0771 | 11.8678 | 21.9378 | 27.9312 | 126.2918 |
| 1.9791 | 15.0 | 3487 | 2.1409 | 34.9493 | 11.9437 | 21.8772 | 28.0146 | 126.3562 |
| 1.9495 | 16.0 | 3720 | 2.1411 | 35.1092 | 11.8562 | 21.9693 | 28.0417 | 126.1502 |
| 1.9495 | 17.0 | 3952 | 2.1408 | 35.3591 | 12.0079 | 22.0824 | 28.0746 | 126.3176 |
| 1.9391 | 18.0 | 4185 | 2.1414 | 35.1091 | 11.904 | 21.9597 | 27.9814 | 126.1373 |
| 1.9391 | 19.0 | 4417 | 2.1422 | 35.2336 | 12.013 | 22.0223 | 27.8814 | 126.3004 |
| 1.9139 | 19.96 | 4640 | 2.1413 | 35.0654 | 11.6563 | 21.7686 | 27.7516 | 126.3262 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3