OpenAssistant LLaMA 30B SFT 7 HF
This in HF format repo of OpenAssistant's LLaMA 30B SFT 7.
It is the result of merging the XORs from the above repo with the original Llama 30B weights.
This is epoch 7 of OpenAssistant's training of a Llama 30B model.
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Original model card
llama-30b-sft-7:
dtype: fp16
log_dir: "llama_log_30b"
learning_rate: 1e-5
model_name: /home/ubuntu/Open-Assistant/model/model_training/.saved/llama-30b-super-pretrain/checkpoint-3500
#model_name: OpenAssistant/llama-30b-super-pretrain
output_dir: llama_model_30b
deepspeed_config: configs/zero3_config_sft.json
weight_decay: 0.0
residual_dropout: 0.0
max_length: 2048
use_flash_attention: true
warmup_steps: 20
gradient_checkpointing: true
gradient_accumulation_steps: 12
per_device_train_batch_size: 2
per_device_eval_batch_size: 3
eval_steps: 101
save_steps: 485
num_train_epochs: 4
save_total_limit: 3
use_custom_sampler: true
sort_by_length: false
#save_strategy: steps
save_strategy: epoch
datasets:
- oasst_export:
lang: "bg,ca,cs,da,de,en,es,fr,hr,hu,it,nl,pl,pt,ro,ru,sl,sr,sv,uk"
input_file_path: 2023-04-12_oasst_release_ready_synth.jsonl.gz
val_split: 0.05
- vicuna:
val_split: 0.05
max_val_set: 800
fraction: 1.0
- dolly15k:
val_split: 0.05
max_val_set: 300
- grade_school_math_instructions:
val_split: 0.05
- code_alpaca:
val_split: 0.05
max_val_set: 250
- OASST dataset paper: https://arxiv.org/abs/2304.07327