README.md

---
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-ja-en
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ruby-rails-fine-tuned-ja-en
  results: []
---

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# ruby-rails-fine-tuned-ja-en

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ja-en](https://huggingface.co/Helsinki-NLP/opus-mt-ja-en).
It achieves the following results on the evaluation set:
- Loss: 1.6714
- Bleu: 0.3300
- Chrf: 64.8493

## Model description

Fine-tuned for Japanese to English translation of the Ruby and Rails documentation.

## Intended uses & limitations

The training dataset (see below) is still very small, so only minor improvements are expected.

## Training and evaluation data

Trained on a custom dataset specifically based on Ruby and Ruby on Rails documentation: https://huggingface.co/datasets/morinoko-inari/ruby-rails-ja-en

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Chrf    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 23   | 1.7593          | 0.3283 | 64.8523 |
| No log        | 2.0   | 46   | 1.6915          | 0.3260 | 64.6705 |
| No log        | 3.0   | 69   | 1.6714          | 0.3300 | 64.8493 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.21.1