---
library_name: transformers
license: apache-2.0
base_model: google/mt5-large
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: 36e4a4f4479205827cbaeb7182497736
  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. -->

# 36e4a4f4479205827cbaeb7182497736

This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the Helsinki-NLP/opus_books [it-sv] dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0411
- Data Size: 1.0
- Epoch Runtime: 37.1142
- Bleu: 7.5054

## 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    | 24.0301         | 0         | 3.2338        | 0.0077  |
| No log        | 1     | 74   | 22.3734         | 0.0078    | 3.4871        | 0.0069  |
| No log        | 2     | 148  | 18.0931         | 0.0156    | 6.8167        | 0.0107  |
| 0.8365        | 3     | 222  | 17.6183         | 0.0312    | 8.9247        | 0.0115  |
| 0.8365        | 4     | 296  | 15.7380         | 0.0625    | 11.1980       | 0.0115  |
| 1.4537        | 5     | 370  | 16.1153         | 0.125     | 14.3266       | 0.0080  |
| 1.4537        | 6     | 444  | 13.7049         | 0.25      | 18.2127       | 0.0068  |
| 3.7567        | 7     | 518  | 4.4408          | 0.5       | 24.1257       | 0.0363  |
| 4.4368        | 8.0   | 592  | 2.5668          | 1.0       | 38.0884       | 0.7065  |
| 3.1454        | 9.0   | 666  | 2.2962          | 1.0       | 35.8996       | 11.8106 |
| 2.8331        | 10.0  | 740  | 2.1845          | 1.0       | 35.5927       | 4.8443  |
| 2.5558        | 11.0  | 814  | 2.1278          | 1.0       | 37.6358       | 5.0953  |
| 2.4679        | 12.0  | 888  | 2.0948          | 1.0       | 38.5283       | 5.5664  |
| 2.2716        | 13.0  | 962  | 2.0673          | 1.0       | 35.9105       | 6.3039  |
| 2.2181        | 14.0  | 1036 | 2.0499          | 1.0       | 37.5357       | 7.0011  |
| 2.0843        | 15.0  | 1110 | 2.0392          | 1.0       | 35.0586       | 6.9639  |
| 2.0004        | 16.0  | 1184 | 2.0340          | 1.0       | 36.1249       | 7.2430  |
| 1.9004        | 17.0  | 1258 | 2.0303          | 1.0       | 35.3188       | 7.2581  |
| 1.8689        | 18.0  | 1332 | 2.0420          | 1.0       | 36.0142       | 7.0671  |
| 1.7816        | 19.0  | 1406 | 2.0426          | 1.0       | 34.6889       | 7.1300  |
| 1.7352        | 20.0  | 1480 | 2.0407          | 1.0       | 36.7340       | 7.3224  |
| 1.65          | 21.0  | 1554 | 2.0411          | 1.0       | 37.1142       | 7.5054  |


### Framework versions

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