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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- distributed_type: multi-GPU
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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:
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- mixed_precision_training: Native AMP
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### Training results
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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: 1.2472
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- F1 Macro: 0.8544
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- F1: 0.8981
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- F1 Neg: 0.8107
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- Acc: 0.8675
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- Prec: 0.8778
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- Recall: 0.9193
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- Mcc: 0.7106
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## Model description
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- distributed_type: multi-GPU
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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: 15
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- mixed_precision_training: Native AMP
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### Training results
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runs/Mar12_15-36-53_tardis/events.out.tfevents.1710254947.tardis.125084.15
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version https://git-lfs.github.com/spec/v1
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oid sha256:b2ed342933eda32352fa9a4ad6d1913e9a8de1644d4b90fc6ec17db7db84b879
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size 699
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