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 1
Browse files- meta_data/meta_s42_e16_cvi3.json +1 -0
- model.safetensors +1 -1
- training_args.bin +1 -1
meta_data/meta_s42_e16_cvi3.json
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{"B-Claim": {"precision": 0.6144200626959248, "recall": 0.5781710914454278, "f1-score": 0.5957446808510639, "support": 339.0}, "B-MajorClaim": {"precision": 0.7910447761194029, "recall": 0.6625, "f1-score": 0.7210884353741497, "support": 160.0}, "B-Premise": {"precision": 0.7529411764705882, "recall": 0.8161530286928799, "f1-score": 0.7832738398776133, "support": 941.0}, "I-Claim": {"precision": 0.6121971950701233, "recall": 0.6132396764580673, "f1-score": 0.6127179923436835, "support": 4698.0}, "I-MajorClaim": {"precision": 0.7631464580617123, "recall": 0.8658777120315582, "f1-score": 0.8112728112728113, "support": 2028.0}, "I-Premise": {"precision": 0.8770213344204376, "recall": 0.8685821950070655, "f1-score": 0.8727813651577132, "support": 14861.0}, "O": {"precision": 0.9097262667443214, "recall": 0.8948725293612145, "f1-score": 0.9022382671480144, "support": 10473.0}, "accuracy": 0.8354328358208956, "macro avg": {"precision": 0.7600710385117873, "recall": 0.7570566047137447, "f1-score": 0.7570167702892928, "support": 33500.0}, "weighted avg": {"precision": 0.8366601162482339, "recall": 0.8354328358208956, "f1-score": 0.8357536689114934, "support": 33500.0}}
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model.safetensors
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