---
license: apache-2.0
base_model: Danish-summarisation/DanSumT5-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: DanSumT5-largeV_26719
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# DanSumT5-largeV_26719

This model is a fine-tuned version of [Danish-summarisation/DanSumT5-large](https://huggingface.co/Danish-summarisation/DanSumT5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2976
- Rouge1: 32.2799
- Rouge2: 8.6728
- Rougel: 18.8723
- Rougelsum: 29.7852
- Gen Len: 126.28

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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   | 200  | 2.5620          | 31.648  | 7.4069 | 17.9711 | 28.7951   | 126.32  |
| No log        | 2.0   | 400  | 2.4824          | 31.8545 | 8.094  | 18.6072 | 29.1646   | 126.77  |
| 2.7655        | 3.0   | 600  | 2.4305          | 32.1209 | 8.5372 | 18.744  | 29.8788   | 125.03  |
| 2.7655        | 4.0   | 800  | 2.3945          | 31.8225 | 8.739  | 18.5656 | 29.7696   | 125.63  |
| 2.4368        | 5.0   | 1000 | 2.3685          | 31.9779 | 8.322  | 18.766  | 29.4834   | 125.32  |
| 2.4368        | 6.0   | 1200 | 2.3522          | 31.4296 | 8.3578 | 18.9591 | 29.2204   | 125.11  |
| 2.4368        | 7.0   | 1400 | 2.3364          | 31.5372 | 8.2997 | 18.9915 | 29.0248   | 123.38  |
| 2.2645        | 8.0   | 1600 | 2.3250          | 31.9344 | 8.596  | 19.0022 | 29.4647   | 125.18  |
| 2.2645        | 9.0   | 1800 | 2.3212          | 31.515  | 8.2166 | 18.7697 | 29.06     | 126.01  |
| 2.134         | 10.0  | 2000 | 2.3117          | 32.0188 | 8.6934 | 19.1051 | 29.6682   | 125.4   |
| 2.134         | 11.0  | 2200 | 2.3064          | 31.8417 | 8.7247 | 18.9249 | 29.5626   | 125.86  |
| 2.134         | 12.0  | 2400 | 2.3062          | 32.2302 | 9.1081 | 19.3087 | 29.9162   | 126.24  |
| 2.0467        | 13.0  | 2600 | 2.3032          | 31.6755 | 8.5093 | 18.8486 | 29.365    | 125.02  |
| 2.0467        | 14.0  | 2800 | 2.3008          | 31.9478 | 8.8669 | 18.9299 | 29.504    | 126.2   |
| 1.9931        | 15.0  | 3000 | 2.2980          | 31.8088 | 8.7506 | 19.1051 | 29.2949   | 126.0   |
| 1.9931        | 16.0  | 3200 | 2.2982          | 32.175  | 8.8114 | 18.7002 | 29.6088   | 126.0   |
| 1.9931        | 17.0  | 3400 | 2.2987          | 32.0016 | 8.7223 | 18.7814 | 29.6822   | 125.66  |
| 1.949         | 18.0  | 3600 | 2.2974          | 32.0515 | 8.6141 | 18.7833 | 29.6024   | 126.31  |
| 1.949         | 19.0  | 3800 | 2.2970          | 32.0716 | 8.6257 | 18.7301 | 29.4506   | 126.15  |
| 1.9257        | 20.0  | 4000 | 2.2976          | 32.2799 | 8.6728 | 18.8723 | 29.7852   | 126.28  |


### Framework versions

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