dusersad12/TextClassifier-BestRun

TextClassifier

Model Description

This is a BERT-based text classification model fine-tuned on a 5-class dataset. The best checkpoint was selected based on validation F1 score across multiple hyperparameter sweeps.

Training Details

• Base Model: bert-base-uncased
• Best Run ID: run-def456
• Best Run Name: sweep-lr5e5-bs16
• Learning Rate: 5e-05
• Batch Size: 16
• Weight Decay: 0.01
• Best Epoch: 10

Evaluation Results

• Validation F1: 0.851
• Validation Accuracy: 0.865
• Final Validation Loss: 0.487

Run Comparison (sorted by val_f1 descending)

Run ID	Run Name	Learning Rate	Batch Size	Weight Decay	Val F1	Val Accuracy	Val Loss	Best Epoch
run-def456	sweep-lr5e5-bs16	5e-05	16	0.01	0.851	0.865	0.487	10
run-pqr678	sweep-lr5e5-bs16-wd005	5e-05	16	0.005	0.841	0.855	0.512	10
run-jkl012	sweep-lr5e5-bs32-wd0	5e-05	32	0.0	0.829	0.841	0.583	8
run-abc123	sweep-lr3e5-bs32	3e-05	32	0.01	0.811	0.826	0.585	10
run-ghi789	sweep-lr2e5-bs64	2e-05	64	0.02	0.782	0.796	0.649	10
run-mno345	sweep-lr1e4-bs32	0.0001	32	0.01	0.735	0.751	0.821	7

Intended Use

This model is intended for text classification tasks with 5 output classes. It should not be used for generating text or for tasks outside its training distribution.

Limitations

The model's performance is benchmark-specific and may not generalize to out-of-distribution inputs or domains not seen during training.

License

This model is released under the MIT License.