distilbert-qasports

This model is a fine-tuned version of distilbert-base-uncased-distilled-squad on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4019
• Exact: 76.8699
• F1: 81.3261
• Total: 15041
• Hasans Exact: 76.8699
• Hasans F1: 81.3261
• Hasans Total: 15041
• Best Exact: 76.8699
• Best Exact Thresh: 0.0
• Best F1: 81.3261
• Best F1 Thresh: 0.0

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:

• learning_rate: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Exact	F1	Total	Hasans Exact	Hasans F1	Hasans Total	Best Exact	Best Exact Thresh	Best F1	Best F1 Thresh
0.6782	0.1325	500	0.6027	74.4099	79.3976	15041	74.4099	79.3976	15041	74.4099	0.0	79.3976	0.0
0.569	0.2649	1000	0.5509	75.1080	80.1014	15041	75.1080	80.1014	15041	75.1080	0.0	80.1014	0.0
0.5821	0.3974	1500	0.5195	75.5535	80.3558	15041	75.5535	80.3558	15041	75.5535	0.0	80.3558	0.0
0.5814	0.5298	2000	0.4890	76.3978	81.0751	15041	76.3978	81.0751	15041	76.3978	0.0	81.0751	0.0
0.5165	0.6623	2500	0.4729	76.2117	80.9615	15041	76.2117	80.9615	15041	76.2117	0.0	80.9615	0.0
0.4822	0.7947	3000	0.4559	76.4976	81.2088	15041	76.4976	81.2088	15041	76.4976	0.0	81.2088	0.0
0.5015	0.9272	3500	0.4343	76.5308	81.0962	15041	76.5308	81.0962	15041	76.5308	0.0	81.0962	0.0
0.36	1.0596	4000	0.4349	76.5308	81.0828	15041	76.5308	81.0828	15041	76.5308	0.0	81.0828	0.0
0.4052	1.1921	4500	0.4257	76.6704	81.1909	15041	76.6704	81.1909	15041	76.6704	0.0	81.1909	0.0
0.36	1.3245	5000	0.4372	77.1624	81.7279	15041	77.1624	81.7279	15041	77.1624	0.0	81.7279	0.0
0.3597	1.4570	5500	0.4281	77.1225	81.7018	15041	77.1225	81.7018	15041	77.1225	0.0	81.7018	0.0
0.3739	1.5894	6000	0.4064	76.8566	81.3582	15041	76.8566	81.3582	15041	76.8566	0.0	81.3582	0.0
0.4176	1.7219	6500	0.4011	76.6438	81.0437	15041	76.6438	81.0437	15041	76.6438	0.0	81.0437	0.0
0.3924	1.8543	7000	0.3985	77.0560	81.4585	15041	77.0560	81.4585	15041	77.0560	0.0	81.4585	0.0
0.3453	1.9868	7500	0.4019	76.8699	81.3261	15041	76.8699	81.3261	15041	76.8699	0.0	81.3261	0.0

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0