gpt2_for_whole_train_result_2_1bce

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0456
• Accuracy: 0.994
• F1: 0.9944

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: 0.0001
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 64
• total_train_batch_size: 4096
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
2.7095	6.8817	50	1.1202	0.652	0.7212
0.2903	13.7634	100	0.1204	0.96	0.9635
0.051	20.6452	150	0.0537	0.985	0.9860
0.021	27.5269	200	0.0396	0.9895	0.9902
0.0088	34.4086	250	0.0438	0.989	0.9897
0.0047	41.2903	300	0.0419	0.9915	0.9921
0.0024	48.1720	350	0.0442	0.993	0.9935
0.0016	55.0538	400	0.0405	0.993	0.9934
0.0008	61.9355	450	0.0425	0.994	0.9944
0.0011	68.8172	500	0.0376	0.994	0.9944
0.0008	75.6989	550	0.0541	0.992	0.9925
0.001	82.5806	600	0.0453	0.9935	0.9939
0.0015	89.4624	650	0.0396	0.994	0.9944
0.0003	96.3441	700	0.0456	0.994	0.9944

Framework versions

• Transformers 4.40.0
• Pytorch 2.4.1+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1