add axolotl config

Goku-8x22B-v0.1.yaml

@@ -0,0 +1,81 @@
+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|>"