---
license: apache-2.0
base_model: emilstabil/mt5-base_V25775
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-base_V25775_V44105
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mt5-base_V25775_V44105

This model is a fine-tuned version of [emilstabil/mt5-base_V25775](https://huggingface.co/emilstabil/mt5-base_V25775) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1019
- Rouge1: 30.2631
- Rouge2: 10.8564
- Rougel: 20.9297
- Rougelsum: 24.8312
- Gen Len: 80.9356

## 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: 3
- eval_batch_size: 3
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.32          | 0.81  | 500   | 2.1435          | 28.7386 | 10.9481 | 20.3975 | 23.8195   | 74.2704 |
| 2.2393        | 1.61  | 1000  | 2.1053          | 29.1856 | 10.7042 | 20.4864 | 24.1221   | 75.515  |
| 2.2124        | 2.42  | 1500  | 2.1157          | 28.6845 | 10.9397 | 20.4075 | 23.9154   | 74.8627 |
| 2.1635        | 3.23  | 2000  | 2.1232          | 28.8373 | 10.8364 | 20.4743 | 24.0269   | 74.1845 |
| 2.1148        | 4.03  | 2500  | 2.1149          | 29.0484 | 11.0898 | 20.6711 | 24.0963   | 73.9571 |
| 2.0904        | 4.84  | 3000  | 2.1101          | 29.5911 | 11.2027 | 20.883  | 24.3776   | 76.8412 |
| 2.0598        | 5.65  | 3500  | 2.1212          | 29.5276 | 10.8551 | 20.5466 | 24.1469   | 78.4506 |
| 2.0596        | 6.45  | 4000  | 2.1368          | 29.8832 | 10.9578 | 20.7962 | 24.4686   | 80.3777 |
| 2.0135        | 7.26  | 4500  | 2.1173          | 29.5314 | 10.6881 | 20.375  | 24.2483   | 81.5751 |
| 2.0085        | 8.06  | 5000  | 2.1050          | 29.7932 | 11.0481 | 20.8481 | 24.5598   | 78.5708 |
| 2.0006        | 8.87  | 5500  | 2.1233          | 30.4225 | 11.3125 | 21.1509 | 24.9171   | 81.3648 |
| 1.9888        | 9.68  | 6000  | 2.1067          | 29.9013 | 10.7672 | 20.6523 | 24.5878   | 78.7897 |
| 1.9496        | 10.48 | 6500  | 2.1036          | 29.7453 | 10.9583 | 20.7396 | 24.3824   | 78.7425 |
| 1.9513        | 11.29 | 7000  | 2.1125          | 29.5484 | 10.752  | 20.4861 | 24.3097   | 79.0558 |
| 1.9476        | 12.1  | 7500  | 2.1014          | 29.6296 | 10.8252 | 20.6412 | 24.2908   | 76.1202 |
| 1.9294        | 12.9  | 8000  | 2.1102          | 29.9456 | 10.9121 | 20.8077 | 24.5787   | 79.515  |
| 1.9036        | 13.71 | 8500  | 2.0977          | 30.1173 | 10.9352 | 20.9176 | 24.9725   | 80.9056 |
| 1.9415        | 14.52 | 9000  | 2.1011          | 29.9247 | 10.8223 | 20.7609 | 24.6858   | 81.103  |
| 1.8959        | 15.32 | 9500  | 2.0998          | 29.8002 | 10.6206 | 20.5674 | 24.6966   | 80.4549 |
| 1.9356        | 16.13 | 10000 | 2.1038          | 30.355  | 11.0359 | 21.0347 | 25.0475   | 80.8927 |
| 1.8958        | 16.94 | 10500 | 2.1029          | 30.3957 | 11.0562 | 21.1067 | 25.1431   | 82.1588 |
| 1.9093        | 17.74 | 11000 | 2.1002          | 30.4669 | 10.9894 | 20.9725 | 24.9598   | 81.1888 |
| 1.8969        | 18.55 | 11500 | 2.1045          | 30.4956 | 10.9426 | 20.9578 | 24.9973   | 81.824  |
| 1.8971        | 19.35 | 12000 | 2.1019          | 30.2631 | 10.8564 | 20.9297 | 24.8312   | 80.9356 |


### Framework versions

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