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
- 16
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
Base model
distilbert/distilgpt2