Instructions to use tweettemposhift/hate-hate_balance_random0_seed2-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_balance_random0_seed2-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_balance_random0_seed2-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_balance_random0_seed2-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_balance_random0_seed2-roberta-base") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 41522a3
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": 0.49649494886398315, "test/eval_f1": 0.6751592356687897, "test/eval_accuracy": 0.8614130434782609, "test/eval_runtime": 0.8564, "test/eval_samples_per_second": 429.689, "test/eval_steps_per_second": 53.711}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3b7a32480dbdb96a5d0096f7468ddf60b6377cfddcb7b420568ccc2ad470f8c7
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size 4536
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