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--- |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-en-ROMANCE |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: seq2seq-finetuned-slang-en |
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results: [] |
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--- |
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# seq2seq-finetuned-slang-en |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ROMANCE](https://huggingface.co/Helsinki-NLP/opus-mt-en-ROMANCE) on a dataset of 1772 messages in slang English, and manually translated into standard English. |
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There are some typos, since this was a first approach. Thus, insults or acronyms are not taken into account. Also, you may confirm mistakes, such as translating 'ya' almost always as 'yes', while it can also be 'you'. |
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These are nuances I am working on. |
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I am also working on this task for other languages, if you like the project, please contact me. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0286 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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This is a prototype. I am working on a better model. The goal would be to finetune a model able to translate slang English into standard English. |
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I am also working on applying it to different languages. |
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## Training and evaluation data |
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The data partition is as follows: 85% train and val, and 15% for testing. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.0844 | 1.33 | 500 | 0.0714 | |
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| 0.0297 | 2.65 | 1000 | 0.0286 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Tokenizers 0.15.1 |
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