Instructions to use SajjadAyoubi/roberta-feature-as-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SajjadAyoubi/roberta-feature-as-text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SajjadAyoubi/roberta-feature-as-text")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SajjadAyoubi/roberta-feature-as-text") model = AutoModelForSequenceClassification.from_pretrained("SajjadAyoubi/roberta-feature-as-text") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
base model: 'HooshvareLab/bert-fa-zwnj-base'
- trained for 1 epoch with 512 as max_length
model performance on the test:
{'eval_loss': 0.33507922291755676,
'eval_roc_auc': 0.9367072003288893,
'eval_f1_score': 0.8655552222174602,
'eval_recall': 0.8747780136007277,
'eval_percision': 0.8565248738284066,
'eval_runtime': 867.3725,
'eval_samples_per_second': 54.228,
'eval_steps_per_second': 1.695,
'epoch': 1.0}
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