---
library_name: transformers
license: apache-2.0
base_model: google/mt5-large
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: 964a2f79c203348bba76d60ca938cd2d
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 964a2f79c203348bba76d60ca938cd2d

This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the Helsinki-NLP/opus_books [fi-fr] dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8123
- Data Size: 1.0
- Epoch Runtime: 43.0591
- Bleu: 6.1264

## 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    | 22.2111         | 0         | 3.7215        | 0.0208 |
| No log        | 1     | 88   | 21.6220         | 0.0078    | 4.5621        | 0.0193 |
| No log        | 2     | 176  | 16.0156         | 0.0156    | 5.8968        | 0.0190 |
| No log        | 3     | 264  | 11.5975         | 0.0312    | 7.7077        | 0.0281 |
| No log        | 4     | 352  | 6.8749          | 0.0625    | 10.3325       | 0.0261 |
| No log        | 5     | 440  | 5.7621          | 0.125     | 13.3582       | 0.0484 |
| 0.9257        | 6     | 528  | 3.2954          | 0.25      | 17.3148       | 0.1578 |
| 1.5513        | 7     | 616  | 2.5954          | 0.5       | 27.3271       | 0.4223 |
| 2.923         | 8.0   | 704  | 2.0603          | 1.0       | 43.4494       | 9.3587 |
| 2.6132        | 9.0   | 792  | 1.9396          | 1.0       | 42.2230       | 3.6443 |
| 2.3564        | 10.0  | 880  | 1.8772          | 1.0       | 41.0739       | 4.0174 |
| 2.1864        | 11.0  | 968  | 1.8413          | 1.0       | 42.9801       | 4.4609 |
| 2.0437        | 12.0  | 1056 | 1.8230          | 1.0       | 41.3114       | 5.4799 |
| 1.9651        | 13.0  | 1144 | 1.8168          | 1.0       | 42.6002       | 5.4061 |
| 1.8622        | 14.0  | 1232 | 1.8016          | 1.0       | 40.8660       | 5.8221 |
| 1.7951        | 15.0  | 1320 | 1.8066          | 1.0       | 43.6785       | 5.9283 |
| 1.7245        | 16.0  | 1408 | 1.8128          | 1.0       | 43.5209       | 6.1232 |
| 1.6505        | 17.0  | 1496 | 1.8127          | 1.0       | 42.7977       | 6.1399 |
| 1.5791        | 18.0  | 1584 | 1.8123          | 1.0       | 43.0591       | 6.1264 |


### Framework versions

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