Instructions to use tweettemposhift/nerd-nerd_temporal-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/nerd-nerd_temporal-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/nerd-nerd_temporal-roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/nerd-nerd_temporal-roberta-large") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/nerd-nerd_temporal-roberta-large") - Notebooks
- Google Colab
- Kaggle
commit files to HF hub
Browse files- summary.json +1 -0
- training_args.bin +3 -0
summary.json
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{"test/eval_loss": 0.41238099336624146, "test/eval_f1": 0.8579061305329095, "test/eval_accuracy": 0.8548440220204206, "test/eval_runtime": 173.3713, "test/eval_samples_per_second": 122.587, "test/eval_steps_per_second": 15.325, "test_1/eval_loss": 0.4086536765098572, "test_1/eval_f1": 0.8619491680380326, "test_1/eval_accuracy": 0.8578957274609449, "test_1/eval_runtime": 44.0703, "test_1/eval_samples_per_second": 120.557, "test_1/eval_steps_per_second": 15.09, "test_2/eval_loss": 0.39932122826576233, "test_2/eval_f1": 0.8585220943186038, "test_2/eval_accuracy": 0.8565782044042913, "test_2/eval_runtime": 43.272, "test_2/eval_samples_per_second": 122.782, "test_2/eval_steps_per_second": 15.368, "test_3/eval_loss": 0.41391950845718384, "test_3/eval_f1": 0.8565072302558397, "test_3/eval_accuracy": 0.8543195934500283, "test_3/eval_runtime": 43.2303, "test_3/eval_samples_per_second": 122.9, "test_3/eval_steps_per_second": 15.383, "test_4/eval_loss": 0.42762669920921326, "test_4/eval_f1": 0.8546320029293298, "test_4/eval_accuracy": 0.8505833646970267, "test_4/eval_runtime": 43.2473, "test_4/eval_samples_per_second": 122.875, "test_4/eval_steps_per_second": 15.377}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:097e4ed36c5ebf2366ca124aac9c1b4c97576cb87d066515576720a969a050cf
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size 4536
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