Token Classification
Transformers
Safetensors
longformer
Generated from Trainer
Eval Results (legacy)
Instructions to use Theoreticallyhugo/longformer-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/longformer-simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Theoreticallyhugo/longformer-simple")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/longformer-simple") model = AutoModelForTokenClassification.from_pretrained("Theoreticallyhugo/longformer-simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 25
Browse files- meta_data/meta_s42_e50_cvi4.json +1 -1
- model.safetensors +1 -1
meta_data/meta_s42_e50_cvi4.json
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{"Claim": {"precision": 0.637881679389313, "recall": 0.6415547024952015, "f1-score": 0.6397129186602871, "support": 4168.0}, "MajorClaim": {"precision": 0.798523664785063, "recall": 0.8545539033457249, "f1-score": 0.8255892255892255, "support": 2152.0}, "O": {"precision": 0.9484063288236643, "recall": 0.8965965748970302, "f1-score": 0.9217740138176956, "support": 9226.0}, "Premise": {"precision": 0.8766328011611031, "recall": 0.9005218255611696, "f1-score": 0.8884167517875383, "support": 12073.0}, "accuracy": 0.8565480285310837, "macro avg": {"precision": 0.8153611185397858, "recall": 0.8233067515747815, "f1-score": 0.8188732274636866, "support": 27619.0}, "weighted avg": {"precision": 0.8584922830101466, "recall": 0.8565480285310837, "f1-score": 0.8571321899510156, "support": 27619.0}}
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model.safetensors
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