Se124M500KInfSimple

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

• Loss: 0.4475

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Use OptimizerNames.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
0.1287	1.0	8317	0.5023
0.1249	2.0	16634	0.4836
0.1214	3.0	24951	0.4746
0.1225	4.0	33268	0.4691
0.1212	5.0	41585	0.4653
0.1192	6.0	49902	0.4625
0.1203	7.0	58219	0.4595
0.1182	8.0	66536	0.4579
0.117	9.0	74853	0.4565
0.1184	10.0	83170	0.4543
0.1165	11.0	91487	0.4539
0.116	12.0	99804	0.4528
0.117	13.0	108121	0.4515
0.1161	14.0	116438	0.4512
0.1149	15.0	124755	0.4510
0.1157	16.0	133072	0.4503
0.1162	17.0	141389	0.4497
0.1155	18.0	149706	0.4497
0.115	19.0	158023	0.4496
0.1156	20.0	166340	0.4488
0.1156	21.0	174657	0.4492
0.114	22.0	182974	0.4483
0.1122	23.0	191291	0.4488
0.1134	24.0	199608	0.4480
0.114	25.0	207925	0.4476
0.1159	26.0	216242	0.4481
0.115	27.0	224559	0.4475
0.1145	28.0	232876	0.4475
0.1141	29.0	241193	0.4477

Framework versions

• PEFT 0.15.1
• Transformers 4.51.3
• Pytorch 2.6.0+cu118
• Datasets 3.5.0
• Tokenizers 0.21.1