Instructions to use tweettemposhift/topic-topic_random2_seed2-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random2_seed2-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random2_seed2-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random2_seed2-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random2_seed2-roberta-base") - 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": 0.1524590402841568, "test/eval_f1": 0.6310679611650486, "test/eval_f1_macro": 0.18938705279569526, "test/eval_accuracy": 0.4224343675417661, "test/eval_runtime": 1.8807, "test/eval_samples_per_second": 222.786, "test/eval_steps_per_second": 14.356}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:484f065326c9eea2c9a1c18bfd2907d6b072174038ac981135618fba2059a3e3
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size 4536
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