This model is a fine-tuned version of sshleifer/tiny-gpt2 on the Gustavosta/Stable-Diffusion-Prompts dataset. It achieves the following results on the evaluation set:

Loss: 10.7918
perplexity: 48618.8756

Intended uses & limitations

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Training and evaluation data

refer to the Gustavosta/Stable-Diffusion-Prompts dataset.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 32
total_train_batch_size: 512
total_eval_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss
10.8201	0.96	16	10.8191
10.8167	1.96	32	10.8145
10.8117	2.96	48	10.8095
10.8058	3.96	64	10.8025
10.7997	4.96	80	10.7989
10.7959	5.96	96	10.7947
10.7934	6.96	112	10.7925
10.7924	7.96	128	10.7919
10.7921	8.96	144	10.7918
10.792	9.96	160	10.7918

Framework versions

Transformers 4.25.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.6.1
Tokenizers 0.13.1

pszemraj/tiny-gpt2-magicprompt

tiny-gpt2-magicprompt