README.md

---
license: cc-by-4.0
base_model: Helsinki-NLP/opus-mt-en-de
tags:
- translation
- generated_from_trainer
model-index:
- name: pokemon-finetuned-opus-mt-en-de
  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. -->

# pokemon-finetuned-opus-mt-en-de

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-de](https://huggingface.co/Helsinki-NLP/opus-mt-en-de) on a dataset of translated Pokemon names.
It achieves the following results on the evaluation set:
- Loss: 0.0554
- Exact Match: 0.9893

## Model description

This model is similar to the [Helsinki-NLP/opus-mt-en-de](https://huggingface.co/Helsinki-NLP/opus-mt-en-de) but it now properly translates Pokemon names.

## Intended uses & limitations

This model is part of this [tutorial repository](https://github.com/ajgrant6/Pokemon_LLM_Finetuner). It is only intended as a proof-of-concept and is not intended for legitimate usage or deployment.

This model has not been tested to see if the fine-tuning process changed anything beyond a few Pokemon-related phrases.

## Training and evaluation data

The model was purposely overfit toward the training data, which was a list of translated Pokemon names from this [forum post](https://www.pokecommunity.com/threads/international-list-of-names-in-csv.460446/) 

## Training procedure

The evaluation and training sets were the same given a list of translated Pokemon names.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1