bart-base-instruct: dolly_hhrlhf
This model is a fine-tuned version of facebook/bart-base on the pszemraj/dolly_hhrlhf-text2text dataset.
Model description
text2text models fine-tuned on a modified dataset for text2text generation based on the relatively more permissive mosaicml/dolly_hhrlhf dataset.
Basic usage in Python:
# pip install -q transformers accelerate
from transformers import pipeline, GenerationConfig
model_name = "pszemraj/bart-base-instruct-dolly_hhrlhf"
assistant = pipeline(
"text2text-generation",
model_name,
device_map="auto"
)
cfg = GenerationConfig.from_pretrained(model_name)
# pass an 'instruction' as the prompt to the pipeline
prompt = "Write a guide on how to become a ninja while working a 9-5 job."
result = assistant(prompt, generation_config=cfg)[0]["generated_text"]
print(result)
using the generation config is optional, can subsitute with other generation params.
Intended uses & limitations
- this is not tuned with RLHF etc, and may output offensive results
- this model is rather small (~600 MB) and therefore it's "cognition" abilities are rather limited.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3.0