Upload best run from sweep (run_008, eval_accuracy=0.901)

README.md

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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.

config.json

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+{
+  "learning_rate": 2e-05,
+  "batch_size": 64,
+  "epochs": 12,
+  "weight_decay": 0.001
+}

metrics.json

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+{
+  "eval_accuracy": 0.901,
+  "eval_loss": 0.245,
+  "f1_score": 0.894,
+  "precision": 0.908,
+  "recall": 0.881
+}

pytorch_model.bin

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+size 23