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justinian336
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chupeto

Fill-Mask
Transformers
PyTorch
TensorFlow
bert
generated_from_keras_callback
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  1. README.md +16 -17
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -5,15 +5,18 @@ tags:
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  model-index:
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  - name: chupeto
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  results: []
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- datasets:
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- - justinian336/salvadoran-news
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- language:
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- - es
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  ---
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- # Chupeto
 
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- Chupeto es una versi贸n del modelo [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) que ha sido afinado en un set de datos que contiene m谩s de 100,000 art铆culos de noticias de medios salvadore帽os.
 
 
 
 
 
 
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  ## Model description
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  ## Intended uses & limitations
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- El modelo puede ser utilizado para codificar textos para realizar tareas diversas, tales como:
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- - B煤squeda
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- - Res煤men de noticias
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- - Generaci贸n de t铆tulos de noticias
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- - Extracci贸n de entidades
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  ## Training and evaluation data
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  | Train Loss | Validation Loss | Epoch |
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  |:----------:|:---------------:|:-----:|
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- | 1.0124 | 0.9384 | 0 |
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- | 1.0008 | 0.9214 | 1 |
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- | 0.9911 | 0.9187 | 2 |
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- | 0.9787 | 0.9114 | 3 |
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  ### Framework versions
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  - Transformers 4.26.1
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  - TensorFlow 2.11.0
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- - Datasets 2.10.0
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- - Tokenizers 0.13.2
 
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  model-index:
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  - name: chupeto
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  results: []
 
 
 
 
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  ---
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+ <!-- This model card has been generated automatically according to the information Keras had access to. You should
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+ probably proofread and complete it, then remove this comment. -->
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+ # chupeto
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+
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+ This model is a fine-tuned version of [justinian336/chupeto](https://huggingface.co/justinian336/chupeto) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 0.9468
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+ - Validation Loss: 0.8882
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+ - Epoch: 3
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  ## Model description
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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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  | Train Loss | Validation Loss | Epoch |
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  |:----------:|:---------------:|:-----:|
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+ | 0.9745 | 0.8988 | 0 |
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+ | 0.9645 | 0.8890 | 1 |
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+ | 0.9574 | 0.8913 | 2 |
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+ | 0.9468 | 0.8882 | 3 |
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  ### Framework versions
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  - Transformers 4.26.1
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  - TensorFlow 2.11.0
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2
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