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axolotl/examples/archived/mpt-7b/config.yml

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base_model: mosaicml/mpt-7b
# optionally might have model_type or tokenizer_type
tokenizer_type: AutoTokenizer
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
trust_remote_code: true # required for mpt as their model class is not merged into transformers yet
load_in_8bit: false
datasets:
- path: vicgalle/alpaca-gpt4
type: alpaca
dataset_prepared_path:
val_set_size: 0.02
adapter:
lora_model_dir:
sequence_len: 2048
max_packed_sequence_len:
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
- q_proj
- v_proj
lora_fan_in_fan_out: false
wandb_project: mpt-alpaca-7b
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
output_dir: ./outputs/mpt-alpaca-7b
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_bnb_8bit
torchdistx_path:
lr_scheduler: cosine
learning_rate: 0.0000002
bf16: auto
tf32: true
resume_from_checkpoint:
logging_steps: 5
gptq_groupsize:
gptq_model_v1:
warmup_ratio: 0.1
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 0.0001
tokens:
pad_token: "<|padding|>"
bos_token: "<|endoftext|>"
eos_token: "<|endoftext|>"
unk_token: "<|endoftext|>"