PEFT
PyTorch
Safetensors
llama
Generated from Trainer
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axolotl config
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base_model: pints-ai/1.5-Pints-16K-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: tangledgroup/tangled-llama-pints-1.5b-v0.1-dataset
type: sharegpt
conversation: chatml
chat_template: chatml
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 3
# optimizer: paged_adamw_32bit
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 15.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 3
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens: