Model save

README.md

@@ -0,0 +1,141 @@
+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: mistralai/Mixtral-8x22B-Instruct-v0.1
+model-index:
+- name: parallel-call-original-4-epoch-mixtral-8x22b-instruct
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.0`
+```yaml
+adapter: qlora
+base_model: mistralai/Mixtral-8x22B-Instruct-v0.1
+bf16: true
+chat_template: inst
+dataset_prepared_path: last_run_prepared
+datasets:
+- conversation: mistral
+  path: ./data/with_function_response/original_clean/function_used_training.jsonl
+  type: sharegpt
+- conversation: mistral
+  path: ./data/with_function_response/original_clean/function_not_used_training.jsonl
+  type: sharegpt
+- conversation: mistral
+  path: ./data/with_function_response/parallel_call/parallel_data_training.jsonl
+  type: sharegpt
+debug: null
+# eval_max_new_tokens: 256
+# eval_steps: 0.2
+# eval_table_size: null
+flash_attention: true
+fp16: false
+gradient_accumulation_steps: 4
+gradient_checkpointing: true
+group_by_length: false
+hub_model_id: liuylhf/parallel-call-original-4-epoch-mixtral-8x22b-instruct
+learning_rate: 0.0002
+load_in_4bit: true
+load_in_8bit: false
+logging_steps: 1
+lora_alpha: 64
+lora_dropout: 0.05
+lora_model_dir: null
+lora_r: 32
+lora_target_modules:
+- q_proj
+- k_proj
+- v_proj
+- o_proj
+lr_scheduler: cosine
+micro_batch_size: 2
+model_config:
+  output_router_logits: true
+model_type: AutoModelForCausalLM
+num_epochs: 1
+optimizer: paged_adamw_8bit
+output_dir: model
+pad_to_sequence_len: true
+sample_packing: true
+save_steps: 0.125
+sequence_len: 4096
+strict: false
+tf32: false
+tokenizer_type: LlamaTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0
+wandb_log_model: end
+wandb_name: more-tools
+wandb_project: function-call
+warmup_steps: 10
+weight_decay: 0.0
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: true
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+
+
+
+```
+
+</details><br>
+
+# parallel-call-original-4-epoch-mixtral-8x22b-instruct
+
+This model is a fine-tuned version of [mistralai/Mixtral-8x22B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1) on an unknown dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 1
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.0

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:080fbe2bdb9d6a009b05783f5869edf4d65a6c4da3227c2918011f674cacfccf
+oid sha256:cdb67a56016fdba0bd91566020dda473d4aed907bc7220c345f154cfe99b849e
 size 278982192