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metadata
language:
  - es
license: gpl-3.0
tags:
  - generated_from_trainer
model-index:
  - name: flisol-cba-martin-fierro
    results: []
widget:
  - text: Aqui me pongo a cantar
    example_title: Inicio del Martin Fierro

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 FLISoL de C贸rdoba, Argentina, de 2023.

Para inicializar el setup hace falta tener instalado y activado git-lfs.

Pueden clonar el repositorio con:

$ git clone https://huggingface.co/crscardellino/flisol-cba-martin-fierro

Y luego crean el entorno e instalan los requerimientos.

$ python -m venv flisol-venv
$ source ./flisol-venv/bin/activate
(flisol-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" @ FLISoL de C贸rdoba, 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