prompts = [
    "Write a creative short story based on the following title:",
    "Here is a title for a story. Craft a short narrative around it:",
    "Using the title given, develop a short story:",
    "Imagine a short story that starts with this title:",
    "Create a brief story with the following title:"
]

Concatenate the prompt, the title and the story like so:

concatenated_texts = [random.choice(prompts) + " " + title + "</s>" + "Story: " + selftext for title, selftext in zip(titles, selftexts)]

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Final results: {'loss': 0.0472, 'learning_rate': 1.4893617021276598e-06, 'epoch': 4.95}

Average results: {'train_runtime': 563.2707, 'train_samples_per_second': 1.687, 'train_steps_per_second': 0.417, 'train_loss': 0.8475136074614018, 'epoch': 4.95}

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2

RichardErkhov/alonzogarbanzo_-_Bloom-1b7-creative-writing-8bits

Original model description:

Bloom-1b7-creative-writing

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
alonzogarbanzo_-_Bloom-1b7-creative-writing-8bits