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