---
license: apache-2.0
base_model: emilstabil/DanSumT5-baseV_38821
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: DanSumT5-baseV_38821V_41166
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# DanSumT5-baseV_38821V_41166

This model is a fine-tuned version of [emilstabil/DanSumT5-baseV_38821](https://huggingface.co/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