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---
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-es-es
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: esp-to-lsm-model
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. -->
# esp-to-lsm-model
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-es](https://huggingface.co/Helsinki-NLP/opus-mt-es-es) on a msl glosses dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4524
- Bleu: 68.8807
## 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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 3.6287 | 1.0 | 75 | 2.6073 | 14.3097 |
| 1.886 | 2.0 | 150 | 1.5408 | 44.9883 |
| 1.2239 | 3.0 | 225 | 1.1446 | 60.7215 |
| 1.0309 | 4.0 | 300 | 0.9445 | 49.9656 |
| 0.7936 | 5.0 | 375 | 0.8136 | 51.1677 |
| 0.6785 | 6.0 | 450 | 0.7128 | 38.5475 |
| 0.571 | 7.0 | 525 | 0.6493 | 49.2921 |
| 0.4767 | 8.0 | 600 | 0.5980 | 67.6139 |
| 0.4361 | 9.0 | 675 | 0.5642 | 74.1258 |
| 0.3873 | 10.0 | 750 | 0.5409 | 73.4943 |
| 0.3141 | 11.0 | 825 | 0.5166 | 56.0140 |
| 0.3238 | 12.0 | 900 | 0.4993 | 75.9506 |
| 0.3202 | 13.0 | 975 | 0.4861 | 76.3040 |
| 0.2779 | 14.0 | 1050 | 0.4757 | 52.8020 |
| 0.2384 | 15.0 | 1125 | 0.4648 | 67.2947 |
| 0.2698 | 16.0 | 1200 | 0.4632 | 52.5347 |
| 0.2495 | 17.0 | 1275 | 0.4568 | 69.9258 |
| 0.2258 | 18.0 | 1350 | 0.4550 | 69.4897 |
| 0.2174 | 19.0 | 1425 | 0.4535 | 67.6997 |
| 0.2184 | 20.0 | 1500 | 0.4524 | 68.8807 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |