Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use dimboump/glue_sst_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dimboump/glue_sst_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dimboump/glue_sst_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dimboump/glue_sst_classifier") model = AutoModelForSequenceClassification.from_pretrained("dimboump/glue_sst_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.9013761467889908, | |
| "eval_f1": 0.9033707865168539, | |
| "eval_loss": 0.2359117567539215, | |
| "eval_runtime": 4.9524, | |
| "eval_samples_per_second": 176.076, | |
| "eval_steps_per_second": 1.413 | |
| } |