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--- |
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library_name: peft |
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base_model: t5-small |
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license: apache-2.0 |
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datasets: |
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- opus100 |
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tags: |
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- translation |
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- safetensors |
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- transformers |
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--- |
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# Model Card for Model ID |
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A language translation model fine-tuned on **opus100** dataset for *English to French* translation. |
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## Model Description |
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- **Model type:** Language Model |
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- **Language(s) (NLP):** [More Information Needed] |
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- **License:** Apache 2.0 |
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- **Finetuned from model:** [T5-small](https://huggingface.co/t5-small) |
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## Uses |
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The model is intended to use for English to French translation related tasks. |
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## How to Get Started with the Model |
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Install necessary libraries |
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``` |
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pip install transformers peft accelerate |
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``` |
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Use the code below to get started with the model. |
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```python |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("dmedhi/eng2french-t5-small") |
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model = AutoModelForSeq2SeqLM.from_pretrained("t5-small") |
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model = PeftModel.from_pretrained(model, "dmedhi/eng2french-t5-small") |
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context = tokenizer(["Do you want coffee?"], return_tensors='pt') |
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output = model.generate(**context) |
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result = tokenizer.decode(output[0], skip_special_tokens=True) |
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print(result) |
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# Output |
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# Tu veux du café? |
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``` |
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## Training Details |
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### Training Data |
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- Dataset used: [Opus100](https://huggingface.co/datasets/opus100) |
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- Subset: "en-fr" |
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## Evaluation |
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- global_step=5000 |
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- training_loss=1.295289501953125 |
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#### Metrics |
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- train_runtime = 1672.4371 |
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- train_samples_per_second = 23.917 |
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- train_steps_per_second = 2.99 |
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- total_flos = 685071170273280.0 |
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- train_loss = 1.295289501953125 |
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- epoch = 20.0 |
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## Compute Instance |
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- Google Colab - T4 GPU (Free) |
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### Framework versions |
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- PEFT 0.7.1 |