Instructions to use aidan-o-brien/recipe-improver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aidan-o-brien/recipe-improver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="aidan-o-brien/recipe-improver")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("aidan-o-brien/recipe-improver") model = AutoModelForQuestionAnswering.from_pretrained("aidan-o-brien/recipe-improver") - Notebooks
- Google Colab
- Kaggle
recipe-improver
This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.5570
- Epoch: 0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 5539, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Epoch |
|---|---|
| 2.5570 | 0 |
Framework versions
- Transformers 4.15.0
- TensorFlow 2.7.0
- Datasets 1.17.0
- Tokenizers 0.10.3
- Downloads last month
- 4