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 12
Browse files- meta_data/meta_s42_e16_cvi2.json +1 -1
- model.safetensors +1 -1
meta_data/meta_s42_e16_cvi2.json
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{"B-Claim": {"precision": 0.5818181818181818, "recall": 0.6056782334384858, "f1-score": 0.5935085007727976, "support": 317.0}, "B-MajorClaim": {"precision": 0.7071823204419889, "recall": 0.8258064516129032, "f1-score": 0.761904761904762, "support": 155.0}, "B-Premise": {"precision": 0.7977011494252874, "recall": 0.8432563791008505, "f1-score": 0.819846426461902, "support": 823.0}, "I-Claim": {"precision": 0.6238979118329466, "recall": 0.6190147329650092, "f1-score": 0.621446729835914, "support": 4344.0}, "I-MajorClaim": {"precision": 0.7945389435989257, "recall": 0.8396404919583728, "f1-score": 0.8164673413063478, "support": 2114.0}, "I-Premise": {"precision": 0.8926267956610965, "recall": 0.8950540163151319, "f1-score": 0.8938387582107079, "support": 13607.0}, "O": {"precision": 0.9125967117988395, "recall": 0.89010729866761, "f1-score": 0.9012117232734437, "support": 8481.0}, "accuracy": 0.8446767869709461, "macro avg": {"precision": 0.7586231449396095, "recall": 0.7883653720083377, "f1-score": 0.7726034631094107, "support": 29841.0}, "weighted avg": {"precision": 0.8453513972849044, "recall": 0.8446767869709461, "f1-score": 0.8448841595054579, "support": 29841.0}}
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