Edit model card

gpt2_dolly_lite

This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.4067

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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
2.708 1.0 1300 2.5611
2.1768 2.0 2600 2.4149
1.7189 3.0 3900 2.4067

USAGE

MODEL = 'distilgpt2'

tokenizer = AutoTokenizer.from_pretrained(MODEL)

tokenizer.pad_token = tokenizer.eos_token

def respond(instruction, generator, _input=None, verbose=False, **options):
    if not _input:
        prompt = f'Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:\n'
    else:
        prompt = f'Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Input: {_input}\n\n### Response:\n'
    if verbose:
        print(prompt)
    generated_texts = generator(
        prompt,
        num_return_sequences=3,
        temperature=options.get('temperature', 0.7),
        max_new_tokens=options.get('max_new_tokens', 128)
    )
    for generated_text in generated_texts:
        print(generated_text['generated_text'].split('### Response:\n')[1])
        print('----')

loaded_model = AutoModelForCausalLM.from_pretrained('Andyrasika/gpt2_dolly_lite')

dolly_lite = pipeline('text-generation', model=loaded_model, tokenizer=tokenizer)

respond(
    'Write me an email to my boss, telling her I quit because I made a cool LLM.', dolly_lite
)

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
Downloads last month
15
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Andyrasika/finetuned-gpt2_dolly_lite

Finetuned
(550)
this model

Dataset used to train Andyrasika/finetuned-gpt2_dolly_lite