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# DanSumT5-base-finetuned-test_6887-finetuned-test_1006

This model is a fine-tuned version of [emilstabil/DanSumT5-base-finetuned-test_6887](https://huggingface.co/emilstabil/DanSumT5-base-finetuned-test_6887) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3820
- Rouge1: 32.4141
- Rouge2: 8.6351
- Rougel: 18.809
- Rougelsum: 29.928
- Gen Len: 126.58

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 100  | 2.4957          | 31.4378 | 7.7648 | 17.9498 | 28.7898   | 126.46  |
| No log        | 2.0   | 200  | 2.4718          | 31.3437 | 7.8788 | 17.9692 | 29.1104   | 126.8   |
| No log        | 3.0   | 300  | 2.4465          | 31.6265 | 7.994  | 18.0599 | 28.8198   | 126.42  |
| No log        | 4.0   | 400  | 2.4250          | 31.6974 | 8.0066 | 18.3127 | 29.2615   | 126.65  |
| 2.4645        | 5.0   | 500  | 2.4195          | 31.8113 | 7.9783 | 18.2827 | 29.1518   | 126.93  |
| 2.4645        | 6.0   | 600  | 2.4089          | 31.803  | 8.3958 | 18.5282 | 29.352    | 125.56  |
| 2.4645        | 7.0   | 700  | 2.4022          | 32.1102 | 8.3678 | 18.6127 | 29.5849   | 126.29  |
| 2.4645        | 8.0   | 800  | 2.3916          | 31.4499 | 7.9365 | 18.3485 | 29.047    | 126.95  |
| 2.4645        | 9.0   | 900  | 2.3893          | 32.5308 | 8.4278 | 18.4242 | 29.8826   | 126.75  |
| 2.2217        | 10.0  | 1000 | 2.3895          | 31.8799 | 7.924  | 18.3784 | 29.2475   | 126.55  |
| 2.2217        | 11.0  | 1100 | 2.3864          | 31.5731 | 8.1294 | 18.6812 | 29.3378   | 126.01  |
| 2.2217        | 12.0  | 1200 | 2.3843          | 32.1814 | 8.5896 | 18.9555 | 29.8291   | 126.04  |
| 2.2217        | 13.0  | 1300 | 2.3807          | 32.1    | 8.5707 | 18.7538 | 29.7206   | 126.29  |
| 2.2217        | 14.0  | 1400 | 2.3809          | 32.3983 | 8.7199 | 18.9381 | 30.0217   | 126.58  |
| 2.1181        | 15.0  | 1500 | 2.3820          | 32.4141 | 8.6351 | 18.809  | 29.928    | 126.58  |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "emilstabil/DanSumT5-base-finetuned-test_6887", "model-index": [{"name": "DanSumT5-base-finetuned-test_6887-finetuned-test_1006", "results": []}]}
transformers pytorch mt5 text2text-generation generated_from_trainer base_model:emilstabil/DanSumT5-base-finetuned-test_6887 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us