---
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-tc-bible-big-mul-mul
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: en_to_dzo_helsinki_nlp_m2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# en_to_dzo_helsinki_nlp_m2

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tc-bible-big-mul-mul](https://huggingface.co/Helsinki-NLP/opus-mt-tc-bible-big-mul-mul) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3012
- Bleu: 2.8367
- Gen Len: 119.2242

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 9
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 0.8419        | 1.0   | 562  | 0.5239          | 0.0    | 121.8458 |
| 0.5144        | 2.0   | 1124 | 0.4316          | 1.0161 | 118.9429 |
| 0.4296        | 3.0   | 1686 | 0.3774          | 0.8574 | 118.6066 |
| 0.3759        | 4.0   | 2248 | 0.3462          | 1.4119 | 118.6577 |
| 0.3351        | 5.0   | 2810 | 0.3250          | 2.0178 | 119.8008 |
| 0.3065        | 6.0   | 3372 | 0.3123          | 2.5655 | 118.7538 |
| 0.2839        | 7.0   | 3934 | 0.3037          | 3.0749 | 118.5455 |
| 0.2665        | 8.0   | 4496 | 0.3023          | 2.9584 | 119.3423 |
| 0.2441        | 9.0   | 5058 | 0.3012          | 2.8367 | 119.2242 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3