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---
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
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