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---
license: apache-2.0
base_model: Danish-summarisation/DanSumT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: DanSumT5-baseV_38821
  results: []
---

<!-- 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-baseV_38821

This model is a fine-tuned version of [Danish-summarisation/DanSumT5-base](https://huggingface.co/Danish-summarisation/DanSumT5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2026
- Rouge1: 34.9358
- Rouge2: 11.6813
- Rougel: 21.4935
- Rougelsum: 27.4979
- 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: 2e-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  | 2.4684          | 33.3966 | 9.9982  | 19.6472 | 27.3865   | 126.8712 |
| No log        | 2.0   | 465  | 2.3905          | 34.2228 | 10.5192 | 20.3584 | 27.4209   | 126.8712 |
| 2.8064        | 3.0   | 697  | 2.3486          | 34.5949 | 11.0682 | 20.8844 | 27.3403   | 126.6738 |
| 2.8064        | 4.0   | 930  | 2.3193          | 34.6865 | 11.0996 | 20.9574 | 27.337    | 126.2318 |
| 2.5767        | 5.0   | 1162 | 2.2963          | 34.3101 | 11.0183 | 20.8461 | 27.155    | 126.721  |
| 2.5767        | 6.0   | 1395 | 2.2774          | 34.9299 | 11.5927 | 21.3549 | 27.7805   | 126.4249 |
| 2.483         | 7.0   | 1627 | 2.2646          | 34.4741 | 11.1383 | 21.2722 | 27.3822   | 126.3004 |
| 2.483         | 8.0   | 1860 | 2.2521          | 34.9384 | 11.2651 | 21.3153 | 27.5792   | 126.9828 |
| 2.4134        | 9.0   | 2092 | 2.2410          | 34.9546 | 11.424  | 21.1427 | 27.6608   | 126.7854 |
| 2.4134        | 10.0  | 2325 | 2.2326          | 34.7566 | 11.5721 | 21.4418 | 27.5167   | 126.7425 |
| 2.3576        | 11.0  | 2557 | 2.2263          | 34.5968 | 11.623  | 21.2384 | 27.365    | 126.4506 |
| 2.3576        | 12.0  | 2790 | 2.2194          | 34.7363 | 11.5612 | 21.47   | 27.6572   | 126.5665 |
| 2.3288        | 13.0  | 3022 | 2.2142          | 34.971  | 11.7203 | 21.49   | 27.7418   | 126.5665 |
| 2.3288        | 14.0  | 3255 | 2.2114          | 34.761  | 11.6621 | 21.3963 | 27.568    | 126.6266 |
| 2.3288        | 15.0  | 3487 | 2.2064          | 34.9197 | 11.5475 | 21.4017 | 27.6388   | 126.3305 |
| 2.2951        | 16.0  | 3720 | 2.2067          | 34.8124 | 11.615  | 21.5177 | 27.605    | 126.3605 |
| 2.2951        | 17.0  | 3952 | 2.2042          | 34.7608 | 11.4738 | 21.3464 | 27.379    | 126.4034 |
| 2.2832        | 18.0  | 4185 | 2.2032          | 34.7593 | 11.6239 | 21.4029 | 27.4669   | 126.2489 |
| 2.2832        | 19.0  | 4417 | 2.2029          | 34.8386 | 11.5919 | 21.4719 | 27.5147   | 126.2318 |
| 2.2571        | 19.96 | 4640 | 2.2026          | 34.9358 | 11.6813 | 21.4935 | 27.4979   | 126.3262 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3