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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: poem-gen-spanish-t5-small
results: []
---
# poem-gen-spanish-t5-small
This model is a fine-tuned version of [flax-community/spanish-t5-small](https://huggingface.co/flax-community/spanish-t5-small) on the [Spanish Poetry Dataset](https://www.kaggle.com/andreamorgar/spanish-poetry-dataset/version/1) dataset.
The model was created during the [First Spanish Hackathon](https://somosnlp.org/hackathon) organized by [Somos NLP](https://somosnlp.org/).
The team who participated was composed by:
- 🇮🇳 [Drishti Sharma](https://huggingface.co/DrishtiSharma)
- 🇪🇸 [Andrea Morales Garzón](https://huggingface.co/andreamorgar)
- Jorge Henao
- 🇨🇺 [Alberto Carmona Barthelemy](https://huggingface.co/milyiyo)
It achieves the following results on the evaluation set:
- Loss: 2.8586
- Perplexity: 17.43
## Model description
The model was trained to generate spanish poems attending to some parameters like style, sentiment, words to include and starting phrase.
Example:
```
poema:
estilo: Pablo Neruda &&
sentimiento: positivo &&
palabras: cielo, luna, mar &&
texto: Todos fueron a verle pasar
```
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 3.1354 | 0.73 | 30000 | 3.0147 |
| 2.9761 | 1.46 | 60000 | 2.9498 |
| 2.897 | 2.19 | 90000 | 2.9019 |
| 2.8292 | 2.93 | 120000 | 2.8792 |
| 2.7774 | 3.66 | 150000 | 2.8738 |
| 2.741 | 4.39 | 180000 | 2.8634 |
| 2.7128 | 5.12 | 210000 | 2.8666 |
| 2.7108 | 5.85 | 240000 | 2.8595 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
|