---
library_name: transformers
license: apache-2.0
base_model: google/mt5-large
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: c7604cf43f2ead5903e79dc76fa69bb7
  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. -->

# c7604cf43f2ead5903e79dc76fa69bb7

This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the Helsinki-NLP/opus_books [fi-no] dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1777
- Data Size: 1.0
- Epoch Runtime: 39.5704
- Bleu: 6.2517

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Bleu   |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:------:|
| No log        | 0     | 0    | 21.3467         | 0         | 3.5736        | 0.0079 |
| No log        | 1     | 85   | 22.9127         | 0.0078    | 4.4974        | 0.0082 |
| No log        | 2     | 170  | 24.4305         | 0.0156    | 5.5673        | 0.0044 |
| No log        | 3     | 255  | 23.3816         | 0.0312    | 8.5154        | 0.0039 |
| No log        | 4     | 340  | 22.7459         | 0.0625    | 11.5559       | 0.0040 |
| 1.5516        | 5     | 425  | 21.5469         | 0.125     | 13.8482       | 0.0033 |
| 1.5516        | 6     | 510  | 20.2011         | 0.25      | 17.5870       | 0.0043 |
| 6.0479        | 7     | 595  | 11.4255         | 0.5       | 26.3378       | 0.0045 |
| 9.8735        | 8.0   | 680  | 3.5418          | 1.0       | 42.3483       | 0.1807 |
| 3.6569        | 9.0   | 765  | 2.5037          | 1.0       | 39.9547       | 4.0870 |
| 2.9705        | 10.0  | 850  | 2.3234          | 1.0       | 38.7879       | 4.5832 |
| 2.7775        | 11.0  | 935  | 2.2432          | 1.0       | 39.1521       | 4.9747 |
| 2.5337        | 12.0  | 1020 | 2.1994          | 1.0       | 40.3694       | 5.1626 |
| 2.4171        | 13.0  | 1105 | 2.1733          | 1.0       | 39.9761       | 5.4123 |
| 2.2872        | 14.0  | 1190 | 2.1624          | 1.0       | 41.8520       | 5.4914 |
| 2.1794        | 15.0  | 1275 | 2.1449          | 1.0       | 39.4007       | 5.7806 |
| 2.0549        | 16.0  | 1360 | 2.1618          | 1.0       | 40.6027       | 5.9617 |
| 1.9814        | 17.0  | 1445 | 2.1540          | 1.0       | 39.2313       | 5.9820 |
| 1.8869        | 18.0  | 1530 | 2.1517          | 1.0       | 40.7726       | 6.0788 |
| 1.8155        | 19.0  | 1615 | 2.1777          | 1.0       | 39.5704       | 6.2517 |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1