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 26
Browse files- meta_data/meta_s42_e50_cvi1.json +1 -1
- model.safetensors +1 -1
meta_data/meta_s42_e50_cvi1.json
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{"B-Claim": {"precision": 0.5510204081632653, "recall": 0.6406779661016949, "f1-score": 0.5924764890282131, "support": 295.0}, "B-MajorClaim": {"precision": 0.7262569832402235, "recall": 0.8333333333333334, "f1-score": 0.7761194029850748, "support": 156.0}, "B-Premise": {"precision": 0.7909090909090909, "recall": 0.8376891334250344, "f1-score": 0.8136272545090181, "support": 727.0}, "I-Claim": {"precision": 0.5972798524665744, "recall": 0.6253922278542119, "f1-score": 0.6110128522579885, "support": 4143.0}, "I-MajorClaim": {"precision": 0.7669053301511536, "recall": 0.8791609667122663, "f1-score": 0.8192054387083068, "support": 2193.0}, "I-Premise": {"precision": 0.9003624647603705, "recall": 0.889755631616652, "f1-score": 0.8950276243093924, "support": 12563.0}, "O": {"precision": 0.9380284594761806, "recall": 0.8936149312377211, "f1-score": 0.9152832276889022, "support": 10180.0}, "accuracy": 0.8501173282215686, "macro avg": {"precision": 0.7529660841666941, "recall": 0.7999463128972735, "f1-score": 0.7746788984981279, "support": 30257.0}, "weighted avg": {"precision": 0.8549286181355421, "recall": 0.8501173282215686, "f1-score": 0.8519390977698099, "support": 30257.0}}
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