Instructions to use dtorber/bert-base-spanish-wwm-cased_K3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/bert-base-spanish-wwm-cased_K3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/bert-base-spanish-wwm-cased_K3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/bert-base-spanish-wwm-cased_K3") model = AutoModelForSequenceClassification.from_pretrained("dtorber/bert-base-spanish-wwm-cased_K3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
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This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- F1 Macro: 0.
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- F1: 0.
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- F1 Neg: 0.
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- Acc: 0.
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- Prec: 0.
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- Recall: 0.
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- Mcc: 0.
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## Model description
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This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3108
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- F1 Macro: 0.8595
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- F1: 0.9001
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- F1 Neg: 0.8190
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- Acc: 0.8712
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- Prec: 0.8872
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- Recall: 0.9134
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- Mcc: 0.7198
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## Model description
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