gpt2_for_whole_train_result_4_1bce

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

• Loss: 0.0332
• 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
0.7029	6.8817	50	0.5150	0.8	0.7923
0.247	13.7634	100	0.0808	0.968	0.9696
0.0457	20.6452	150	0.0521	0.9845	0.9853
0.0164	27.5269	200	0.0379	0.99	0.9906
0.0062	34.4086	250	0.0287	0.9945	0.9948
0.0029	41.2903	300	0.0373	0.9935	0.9939
0.0021	48.1720	350	0.0336	0.995	0.9953
0.0009	55.0538	400	0.0351	0.993	0.9934
0.0005	61.9355	450	0.0374	0.994	0.9944
0.0011	68.8172	500	0.0378	0.994	0.9944
0.0016	75.6989	550	0.0306	0.996	0.9962
0.0004	82.5806	600	0.0363	0.9955	0.9958
0.0002	89.4624	650	0.0439	0.995	0.9953
0.001	96.3441	700	0.0332	0.994	0.9944

Framework versions

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