| #Mistral-7b | |
| base_model: mistralai/Mistral-7B-v0.1 | |
| model_type: MistralForCausalLM | |
| tokenizer_type: LlamaTokenizer | |
| load_in_8bit: true | |
| load_in_4bit: false | |
| strict: false | |
| datasets: | |
| - path: tilemachos/Demo-Dataset #Path to json dataset file in huggingface | |
| #for type,conversation arguments read axolotl readme and pick what is suited for your project, I wanted a chatbot and put sharegpt and chatml | |
| type: sharegpt | |
| conversation: chatml | |
| dataset_prepared_path: tilemachos/Demo-Dataset #Path to json dataset file in huggingface | |
| val_set_size: 0.05 | |
| output_dir: ./out | |
| #using lora for lower cost | |
| adapter: lora | |
| lora_r: 8 | |
| lora_alpha: 16 | |
| lora_dropout: 0.05 | |
| lora_target_modules: | |
| - q_proj | |
| - v_proj | |
| sequence_len: 512 | |
| sample_packing: false | |
| pad_to_sequence_len: true | |
| wandb_project: | |
| wandb_entity: | |
| wandb_watch: | |
| wandb_name: | |
| wandb_log_model: | |
| #only 2 epochs because of small dataset | |
| gradient_accumulation_steps: 3 | |
| micro_batch_size: 2 | |
| num_epochs: 2 | |
| optimizer: adamw_bnb_8bit | |
| lr_scheduler: cosine | |
| learning_rate: 0.0002 | |
| train_on_inputs: false | |
| group_by_length: false | |
| bf16: true | |
| fp16: false | |
| tf32: false | |
| gradient_checkpointing: true | |
| early_stopping_patience: | |
| resume_from_checkpoint: | |
| local_rank: | |
| logging_steps: 1 | |
| xformers_attention: | |
| flash_attention: true | |
| warmup_steps: 10 | |
| evals_per_epoch: 4 | |
| eval_table_size: | |
| eval_max_new_tokens: 128 | |
| saves_per_epoch: 1 | |
| debug: | |
| #default deepspeed, can use more aggresive if needed like zero2, zero3 | |
| deepspeed: deepspeed_configs/zero1.json | |
| weight_decay: 0.0 | |
| fsdp: | |
| fsdp_config: | |
| special_tokens: | |
| bos_token: "<s>" | |
| eos_token: "</s>" | |
| unk_token: "<unk>" | |