vi_gpt

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

• Loss: 3.0359

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: 0.0005
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• training_steps: 2561
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.7072	0.0200	256	4.4571
4.0563	0.0400	512	3.9044
3.7398	0.0600	768	3.6152
3.569	0.0800	1024	3.4209
3.4202	0.1001	1280	3.2897
3.319	0.1201	1536	3.1876
3.2328	0.1401	1792	3.1171
3.1905	0.1601	2048	3.0668
3.1555	0.1801	2304	3.0411
3.1468	0.2001	2560	3.0359

Framework versions

• Transformers 4.42.3
• Pytorch 2.2.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1