tinyllama-airoboros – AI Model by openaccess-ai-collective | AlphaNeural AI

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tinyllama-airoboros

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TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T

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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