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 21
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": 0.5819801980198019, "recall": 0.7051343570057581, "f1-score": 0.6376654371881102, "support": 4168.0}, "MajorClaim": {"precision": 0.7559021922428331, "recall": 0.83317843866171, "f1-score": 0.792661361626879, "support": 2152.0}, "O": {"precision": 0.9542405366554864, "recall": 0.8634294385432474, "f1-score": 0.9065665187208377, "support": 9226.0}, "Premise": {"precision": 0.8881762174023125, "recall": 0.8716971755156133, "f1-score": 0.8798595435164284, "support": 12073.0}, "accuracy": 0.8407980013758645, "macro avg": {"precision": 0.7950747860801084, "recall": 0.8183598524315823, "f1-score": 0.8041882152630638, "support": 27619.0}, "weighted avg": {"precision": 0.8537300281304444, "recall": 0.8407980013758645, "f1-score": 0.8454369732073347, "support": 27619.0}}
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model.safetensors
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