Instructions to use tweettemposhift/hate-hate_temporal-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_temporal-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_temporal-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_temporal-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_temporal-bernice") - Notebooks
- Google Colab
- Kaggle
| {"test/eval_loss": 0.720626711845398, "test/eval_f1": 0.43340857787810383, "test/eval_accuracy": 0.8298305084745763, "test/eval_runtime": 2.2688, "test/eval_samples_per_second": 650.137, "test/eval_steps_per_second": 81.543, "test_1/eval_loss": 0.8103896379470825, "test_1/eval_f1": 0.39999999999999997, "test_1/eval_accuracy": 0.8125, "test_1/eval_runtime": 0.5884, "test_1/eval_samples_per_second": 625.433, "test_1/eval_steps_per_second": 78.179, "test_2/eval_loss": 0.6386004090309143, "test_2/eval_f1": 0.4600000000000001, "test_2/eval_accuracy": 0.8532608695652174, "test_2/eval_runtime": 0.572, "test_2/eval_samples_per_second": 643.336, "test_2/eval_steps_per_second": 80.417, "test_3/eval_loss": 0.5508636832237244, "test_3/eval_f1": 0.5555555555555556, "test_3/eval_accuracy": 0.8695652173913043, "test_3/eval_runtime": 0.5737, "test_3/eval_samples_per_second": 641.454, "test_3/eval_steps_per_second": 80.182, "test_4/eval_loss": 0.8813430666923523, "test_4/eval_f1": 0.3333333333333333, "test_4/eval_accuracy": 0.784366576819407, "test_4/eval_runtime": 0.5869, "test_4/eval_samples_per_second": 632.147, "test_4/eval_steps_per_second": 80.083} |