---
base_model: samzirbo/mT5.en-es.pretrained
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5.gendered
  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. -->

# mt5.gendered

This model is a fine-tuned version of [samzirbo/mT5.en-es.pretrained](https://huggingface.co/samzirbo/mT5.en-es.pretrained) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5115
- Bleu: 38.4985
- Meteor: 0.6605
- Chrf++: 60.6076

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- training_steps: 30000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Bleu    | Meteor | Chrf++  |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:------:|:-------:|
| 4.0658        | 0.3215 | 3000  | 2.1146          | 29.6159 | 0.587  | 53.1876 |
| 2.3311        | 0.6431 | 6000  | 1.8553          | 33.4209 | 0.6198 | 56.5789 |
| 2.0997        | 0.9646 | 9000  | 1.7308          | 35.2211 | 0.6359 | 58.0995 |
| 1.9354        | 1.2862 | 12000 | 1.6645          | 36.311  | 0.6437 | 58.9512 |
| 1.8583        | 1.6077 | 15000 | 1.6007          | 37.0671 | 0.6512 | 59.446  |
| 1.8043        | 1.9293 | 18000 | 1.5639          | 37.7823 | 0.6553 | 60.0906 |
| 1.728         | 2.2508 | 21000 | 1.5318          | 37.9166 | 0.6565 | 60.1504 |
| 1.6989        | 2.5723 | 24000 | 1.5188          | 38.4261 | 0.6603 | 60.5626 |
| 1.6854        | 2.8939 | 27000 | 1.5115          | 38.5249 | 0.6607 | 60.6204 |
| 1.6696        | 3.2154 | 30000 | 1.5115          | 38.4985 | 0.6605 | 60.6076 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1