Hugging Face: IA Colaborativa
En este repositorio estar谩 disponible el c贸digo y modelo que entren茅 para la charla "Hugging Face: IA Colaborativa" del XI Congreso de Innovaci贸n, Ambiente e Ingenier铆a, de la Facultad de Ciencias Exactas, F铆sicas y Naturales, de la Universidad Nacional de C贸rdoba, Argentina, en 2023.
Para inicializar el setup hace falta tener instalado y activado
git-lfs.
Pueden clonar el repositorio con:
$ git clone https://huggingface.co/crscardellino/xi-ciai-cba-martin-fierro
Y luego crean el entorno e instalan los requerimientos.
$ python -m venv venv
$ source ./venv/bin/activate
(venv) $ pip install -r requirements.txt
El c贸digo est谩 probado con Python 3.10, pero deber铆a funcionar con Python >= 3.8. En los requerimientos est谩 organizado para instalar PyTorch v2.0.0 para cpu, pero pueden ajustarlo para utilizar GPUs suponiendo que cumplan los requerimientos de CUDA.
Model Specifications (Auto Generated)
This model is a fine-tuned version of
DeepESP/gpt2-spanish on the
./data/martin-fierro_train.txt dataset. It achieves the following results on
the evaluation set:
- Loss: 3.9067
Model description
GPT-2 model finetuned on the poem "El Gaucho Martin Fierro"
Intended uses & limitations
This was trained for the talk "Hugging Face: IA Colaborativa" @ XI Congreso de Innovaci贸n, Ambiente e Ingenier铆a, Argentina, 2023.
Training and evaluation data
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-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
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.3864 | 1.0 | 18 | 4.2025 |
| 3.948 | 2.0 | 36 | 4.0440 |
| 3.7962 | 3.0 | 54 | 3.9804 |
| 3.6105 | 4.0 | 72 | 3.9458 |
| 3.4444 | 5.0 | 90 | 3.9280 |
| 3.3855 | 6.0 | 108 | 3.9192 |
| 3.3142 | 7.0 | 126 | 3.9091 |
| 3.2192 | 8.0 | 144 | 3.9074 |
| 3.1615 | 9.0 | 162 | 3.9070 |
| 3.1637 | 10.0 | 180 | 3.9067 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cpu
- Datasets 2.11.0
- Tokenizers 0.13.3
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