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
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license: apache-2.0
library_name: transformers
tags:
- sweep
- fine-tuned
---
# 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
```python
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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