Token Classification
Transformers
Safetensors
longformer
Generated from Trainer
Eval Results (legacy)
Instructions to use Theoreticallyhugo/longformer-full_labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/longformer-full_labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Theoreticallyhugo/longformer-full_labels")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/longformer-full_labels") model = AutoModelForTokenClassification.from_pretrained("Theoreticallyhugo/longformer-full_labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 16
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-Claim": {"precision": 0.5662251655629139, "recall": 0.602112676056338, "f1-score": 0.5836177474402731, "support": 284.0}, "B-MajorClaim": {"precision": 0.7094594594594594, "recall": 0.7446808510638298, "f1-score": 0.726643598615917, "support": 141.0}, "B-Premise": {"precision": 0.766042780748663, "recall": 0.809322033898305, "f1-score": 0.7870879120879121, "support": 708.0}, "I-Claim": {"precision": 0.5981858298602599, "recall": 0.5984792739759627, "f1-score": 0.5983325159391859, "support": 4077.0}, "I-MajorClaim": {"precision": 0.7981220657276995, "recall": 0.7559288537549407, "f1-score": 0.7764526769855367, "support": 2024.0}, "I-Premise": {"precision": 0.8736565560066873, "recall": 0.8971550032701112, "f1-score": 0.885249868914613, "support": 12232.0}, "O": {"precision": 0.9181542958555173, "recall": 0.8912646939602756, "f1-score": 0.9045096930117758, "support": 9868.0}, "accuracy": 0.8382082225403968, "macro avg": {"precision": 0.7471208790316002, "recall": 0.7569919122828231, "f1-score": 0.751699144713602, "support": 29334.0}, "weighted avg": {"precision": 0.8387644471781172, "recall": 0.8382082225403968, "f1-score": 0.838292846606077, "support": 29334.0}}
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