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 6
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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{"Claim": {"precision": 0.5325670498084292, "recall": 0.6848897231346786, "f1-score": 0.5991994252283692, "support": 4262.0}, "MajorClaim": {"precision": 0.7400087834870444, "recall": 0.7782909930715936, "f1-score": 0.7586672669968483, "support": 2165.0}, "O": {"precision": 0.9212211784799317, "recall": 0.8745439805431698, "f1-score": 0.8972759409440632, "support": 9868.0}, "Premise": {"precision": 0.9062909567496723, "recall": 0.8485313290896541, "f1-score": 0.8764605695726225, "support": 13039.0}, "accuracy": 0.8283220835890094, "macro avg": {"precision": 0.7750219921312693, "recall": 0.796564006459774, "f1-score": 0.7829008006854759, "support": 29334.0}, "weighted avg": {"precision": 0.8447418748493872, "recall": 0.8283220835890094, "f1-score": 0.8344852708551485, "support": 29334.0}}
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model.safetensors
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