Token Classification
Transformers
Safetensors
longformer
Generated from Trainer
Eval Results (legacy)
Instructions to use Theoreticallyhugo/longformer-spans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/longformer-spans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Theoreticallyhugo/longformer-spans")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/longformer-spans") model = AutoModelForTokenClassification.from_pretrained("Theoreticallyhugo/longformer-spans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 9
Browse files- meta_data/meta_s42_e20_cvi0.json +1 -1
- model.safetensors +1 -1
meta_data/meta_s42_e20_cvi0.json
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{"B": {"precision": 0.8464135021097047, "recall": 0.8852603706972639, "f1-score": 0.8654012079378774, "support": 1133.0}, "I": {"precision": 0.9316216786166175, "recall": 0.9638902525500463, "f1-score": 0.9474813007694164, "support": 18333.0}, "O": {"precision": 0.9268053588933667, "recall": 0.8622821240372922, "f1-score": 0.8933802299333298, "support": 9868.0}, "accuracy": 0.9266721210881571, "macro avg": {"precision": 0.9016135132065629, "recall": 0.9038109157615342, "f1-score": 0.9020875795468745, "support": 29334.0}, "weighted avg": {"precision": 0.9267103706800465, "recall": 0.9266721210881571, "f1-score": 0.9261113508073029, "support": 29334.0}}
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model.safetensors
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