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