Edit model card

Built with Axolotl

airoboros-lora-out

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T on the jondurbin/airoboros-3.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7230

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

https://wandb.ai/wing-lian/airoboros-tinyllama

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.999,0.95) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.9777 0.0 1 1.0628
0.6566 0.5 379 0.7230

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.16.0
  • Tokenizers 0.15.0

Training procedure

The following bitsandbytes quantization config was used during training:

  • quant_method: bitsandbytes
  • load_in_8bit: True
  • load_in_4bit: False
  • llm_int8_threshold: 6.0
  • llm_int8_skip_modules: None
  • llm_int8_enable_fp32_cpu_offload: False
  • llm_int8_has_fp16_weight: False
  • bnb_4bit_quant_type: fp4
  • bnb_4bit_use_double_quant: False
  • bnb_4bit_compute_dtype: float32

Framework versions

  • PEFT 0.6.0
Downloads last month
0
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 openaccess-ai-collective/tinyllama-airoboros