File size: 1,606 Bytes
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base_model: v2ray/Mixtral-8x22B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: philschmid/guanaco-sharegpt-style
type: sharegpt
prompt_style: chatml
dataset_prepared_path: last_run_prepared
val_set_size: 0
output_dir: ./models/Goku-8x22B-v0.1
## You can optionally freeze the entire model and unfreeze a subset of parameters
unfrozen_parameters:
# - ^lm_head.weight$
# - ^model.embed_tokens.weight$[:32000]
# - model.layers.2[0-9]+.block_sparse_moe.gate
# - model.layers.2[0-9]+.block_sparse_moe.experts
# - model.layers.3[0-9]+.block_sparse_moe.gate
# - model.layers.3[0-9]+.block_sparse_moe.experts
model_config:
output_router_logits: true
sequence_len: 2048
sample_packing: false
pad_to_sequence_len: true
adapter: qlora
lora_model_dir:
lora_r: 16
lora_alpha: 8
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
gradient_accumulation_steps: 4
micro_batch_size: 6
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs:
group_by_length: false
bf16: auto
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
weight_decay: 0.0
special_tokens:
eos_token: "<|im_end|>"
tokens:
- "<|im_start|>" |