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base_model: mistralai/Mistral-7B-Instruct-v0.3
# optionally might have model_type or tokenizer_type
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
# Automatically upload checkpoint and final model to HF
hub_model_id: AiAF/QLoRA-Finetune-LMTV-TM-9-2320-365-10
load_in_8bit: false
load_in_4bit: true
datasets:
- path: AiAF/TM_plain_qa_list_with_special_tokens.jsonl
ds_type: json
type: chat_template
chat_template: chatml
field_messages: conversations
message_field_role: from
message_field_content: value
roles:
user:
- human
assistant:
- gpt
system:
- system
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./TM-9-2320-365-10_V11
save_total_limit: 100
adapter: qlora
lora_model_dir:
sequence_len: 2048
sample_packing: true
pad_to_sequence_len: true
adapter: qlora
lora_r: 256
lora_alpha: 512
lora_dropout: 0.05
#lora_target_linear: true
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
wandb_project: "LLM-Pretraining"
wandb_watch: "all"
wandb_name: "LMTV-TM-V11"
wandb_log_model: "false"
wandb_run_id: "LMTV-TM-V11"
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 30
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005
bf16: auto
tf32: false
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 5
saves_per_epoch: 2
weight_decay: 0.0
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
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