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---
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-es-es
tags:
- generated_from_trainer
model-index:
- name: '6000'
  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. -->

# 6000

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-es](https://huggingface.co./Helsinki-NLP/opus-mt-es-es) on the English-ASL glosses dataset and spanish-MSL glosses dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2172
- Model Preparation Time: 0.0055
- Bleu Msl: 90.1233
- Bleu Asl: 0
- Ter Msl: 6.3523
- Ter Asl: 100

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- 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
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu Msl | Bleu Asl | Ter Msl  | Ter Asl |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:--------:|:--------:|:-------:|
| No log        | 1.0   | 150  | 2.1707          | 0.0055                 | 6.2392   | 23.0477  | 102.9488 | 79.8599 |
| No log        | 2.0   | 300  | 1.5545          | 0.0055                 | 12.5922  | 39.9535  | 98.5256  | 65.6743 |
| No log        | 3.0   | 450  | 1.1397          | 0.0055                 | 53.7526  | 56.8191  | 35.1258  | 34.5009 |
| 2.0124        | 4.0   | 600  | 0.8560          | 0.0055                 | 61.3665  | 58.7258  | 26.5395  | 33.1874 |
| 2.0124        | 5.0   | 750  | 0.6526          | 0.0055                 | 66.5262  | 60.0265  | 23.0703  | 32.7496 |
| 2.0124        | 6.0   | 900  | 0.5405          | 0.0055                 | 42.9331  | 69.2419  | 32.0035  | 20.7531 |
| 0.7028        | 7.0   | 1050 | 0.4769          | 0.0055                 | 62.3002  | 73.9626  | 22.4631  | 16.9002 |
| 0.7028        | 8.0   | 1200 | 0.4427          | 0.0055                 | 72.1107  | 84.5297  | 16.9991  | 8.0560  |
| 0.7028        | 9.0   | 1350 | 0.4153          | 0.0055                 | 74.8931  | 83.3473  | 16.1318  | 9.3695  |
| 0.3613        | 10.0  | 1500 | 0.3961          | 0.0055                 | 74.8480  | 85.2817  | 15.0911  | 8.4063  |
| 0.3613        | 11.0  | 1650 | 0.3794          | 0.0055                 | 75.4490  | 84.4129  | 15.1778  | 8.4939  |
| 0.3613        | 12.0  | 1800 | 0.3563          | 0.0055                 | 76.8164  | 86.0871  | 13.7901  | 7.6182  |
| 0.3613        | 13.0  | 1950 | 0.3277          | 0.0055                 | 78.1801  | 85.5103  | 13.5299  | 7.9685  |
| 0.2432        | 14.0  | 2100 | 0.3070          | 0.0055                 | 78.6695  | 86.9448  | 13.2697  | 7.5306  |
| 0.2432        | 15.0  | 2250 | 0.2972          | 0.0055                 | 77.6165  | 86.1077  | 13.5299  | 7.7058  |
| 0.2432        | 16.0  | 2400 | 0.2917          | 0.0055                 | 78.0856  | 86.5549  | 13.0095  | 7.5306  |
| 0.1592        | 17.0  | 2550 | 0.2855          | 0.0055                 | 77.3656  | 86.8329  | 13.2697  | 7.2680  |
| 0.1592        | 18.0  | 2700 | 0.2804          | 0.0055                 | 78.3336  | 54.3313  | 12.9228  | 50.6130 |
| 0.1592        | 19.0  | 2850 | 0.2791          | 0.0055                 | 77.4559  | 87.1498  | 13.2697  | 7.2680  |
| 0.1188        | 20.0  | 3000 | 0.2749          | 0.0055                 | 78.0130  | 54.3314  | 12.9228  | 51.0508 |
| 0.1188        | 21.0  | 3150 | 0.2717          | 0.0055                 | 78.2950  | 53.8351  | 12.5759  | 51.3135 |
| 0.1188        | 22.0  | 3300 | 0.2710          | 0.0055                 | 78.2663  | 54.3637  | 12.6626  | 50.8757 |
| 0.1188        | 23.0  | 3450 | 0.2686          | 0.0055                 | 77.8997  | 54.1712  | 13.0095  | 50.8757 |
| 0.0992        | 24.0  | 3600 | 0.2669          | 0.0055                 | 79.2314  | 54.3758  | 12.2290  | 51.0508 |
| 0.0992        | 25.0  | 3750 | 0.2656          | 0.0055                 | 78.2862  | 54.2965  | 12.5759  | 51.1384 |
| 0.0992        | 26.0  | 3900 | 0.2643          | 0.0055                 | 78.9745  | 54.2624  | 12.4024  | 50.8757 |
| 0.0889        | 27.0  | 4050 | 0.2651          | 0.0055                 | 79.3330  | 54.3778  | 12.1422  | 50.9632 |
| 0.0889        | 28.0  | 4200 | 0.2643          | 0.0055                 | 78.4405  | 54.3716  | 12.3157  | 50.9632 |
| 0.0889        | 29.0  | 4350 | 0.2639          | 0.0055                 | 78.5866  | 54.3716  | 12.3157  | 50.9632 |
| 0.083         | 30.0  | 4500 | 0.2639          | 0.0055                 | 78.5866  | 54.3716  | 12.3157  | 50.9632 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0