Instructions to use dusersad12/SweepBestModel-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/SweepBestModel-TestRepo with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dusersad12/SweepBestModel-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
SweepBestModel
This model was selected as the best checkpoint from a hyperparameter sweep over 8 runs. It achieved the highest evaluation accuracy across all configurations tested.
Model Details
- Model type: Encoder-only transformer
- Training objective: Sequence classification
- Sweep strategy: Bayesian optimization
Evaluation Results
| Metric | Value |
|---|---|
| eval_accuracy | 0.901 |
| eval_loss | 0.245 |
| f1_score | 0.894 |
| precision | 0.908 |
| recall | 0.881 |
Training Configuration
The best run was trained with the following hyperparameters:
| Parameter | Value |
|---|---|
| learning_rate | 2e-05 |
| batch_size | 64 |
| epochs | 12 |
| weight_decay | 0.001 |
Usage
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("SweepBestModel-TestRepo")
tokenizer = AutoTokenizer.from_pretrained("SweepBestModel-TestRepo")
License
This model is licensed under the Apache-2.0 License.
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