license: mit
tags:
- generated_from_trainer
- pytorch
model-index:
- name: dolly-v2-3-openassistant-guanaco
results: []
datasets:
- timdettmers/openassistant-guanaco
library_name: peft
pipeline_tag: text-generation
dolly-v2-3-openassistant-guanaco
This model is a fine-tuned version of databricks/dolly-v2-3b on timdettmers/openassistant-guanaco dataset.
Model description
This is a PEFT model, hence the model file and the config files are
- adapter_model.bin
- adapter_config.bin
This fined-tuned model was created with the following bitsandbytes config
BitsAndBytesConfig(load_in_8bit = True, bnb_4bit_quant_type = 'nf4', bnb_4bit_compute_type = torch.bfloat16, bnb_4bit_use_double_quant = True)
The peft_config is as follows:
peft_config = LoraConfig(
lora_alpha=16,
lora_dropout = 0.1,
r = 64,
bias = "none",
task_type = "CAUSAL_LM",
target_modules = [
'query_key_value',
'dense',
'dense_h_to_4h',
'dense_4h_to_h'
]
)
Intended uses & limitations
Model is intended for fair use only.
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 100
Training results
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3