---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: eng_spa_seq2seq
  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. -->

# eng_spa_seq2seq

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0656

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2281        | 0.032 | 500   | 0.2171          |
| 0.194         | 0.064 | 1000  | 0.1832          |
| 0.1684        | 0.096 | 1500  | 0.1612          |
| 0.1583        | 0.128 | 2000  | 0.1476          |
| 0.1451        | 0.16  | 2500  | 0.1344          |
| 0.1371        | 0.192 | 3000  | 0.1238          |
| 0.1286        | 0.224 | 3500  | 0.1164          |
| 0.1231        | 0.256 | 4000  | 0.1099          |
| 0.1191        | 0.288 | 4500  | 0.1048          |
| 0.1119        | 0.32  | 5000  | 0.0997          |
| 0.1072        | 0.352 | 5500  | 0.0956          |
| 0.1073        | 0.384 | 6000  | 0.0917          |
| 0.0961        | 0.416 | 6500  | 0.0887          |
| 0.0983        | 0.448 | 7000  | 0.0865          |
| 0.0942        | 0.48  | 7500  | 0.0834          |
| 0.0921        | 0.512 | 8000  | 0.0814          |
| 0.0901        | 0.544 | 8500  | 0.0792          |
| 0.0853        | 0.576 | 9000  | 0.0771          |
| 0.0846        | 0.608 | 9500  | 0.0761          |
| 0.0823        | 0.64  | 10000 | 0.0739          |
| 0.0823        | 0.672 | 10500 | 0.0727          |
| 0.0824        | 0.704 | 11000 | 0.0717          |
| 0.081         | 0.736 | 11500 | 0.0709          |
| 0.079         | 0.768 | 12000 | 0.0695          |
| 0.0777        | 0.8   | 12500 | 0.0686          |
| 0.0759        | 0.832 | 13000 | 0.0676          |
| 0.0769        | 0.864 | 13500 | 0.0672          |
| 0.0781        | 0.896 | 14000 | 0.0666          |
| 0.0747        | 0.928 | 14500 | 0.0662          |
| 0.0757        | 0.96  | 15000 | 0.0658          |
| 0.0783        | 0.992 | 15500 | 0.0656          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3