organize the axolotl.yml and adapters, set cache
Browse files- README.md +4 -97
- adapter_model.bin +0 -0
- adapter_config.json → adapters/adapter_config.json +0 -0
- adapter_model.safetensors → adapters/adapter_model.safetensors +0 -0
- config.json +1 -1
- configs/mixtral.yml +90 -0
- training_args.bin +0 -3
README.md
CHANGED
@@ -3,9 +3,11 @@ library_name: peft
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base_model: mistralai/Mixtral-8x7B-v0.1
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---
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#
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@@ -217,99 +219,4 @@ The following `bitsandbytes` quantization config was used during training:
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### Framework versions
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- PEFT 0.6.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.6.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.6.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.6.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.6.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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-
- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.6.0
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base_model: mistralai/Mixtral-8x7B-v0.1
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---
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# SlimOrca Mixtral 8x7B
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[<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)
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Official release of the SlimOrca Mixtral finetune. More details to come.
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### Framework versions
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- PEFT 0.6.0
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adapter_model.bin
DELETED
File without changes
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adapter_config.json → adapters/adapter_config.json
RENAMED
File without changes
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adapter_model.safetensors → adapters/adapter_model.safetensors
RENAMED
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config.json
CHANGED
@@ -37,6 +37,6 @@
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.0.dev0",
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"use_cache":
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"vocab_size": 32002
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}
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.0.dev0",
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"use_cache": true,
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"vocab_size": 32002
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}
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configs/mixtral.yml
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base_model: mistralai/Mixtral-8x7B-v0.1
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model_type: AutoModelForCausalLM
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tokenizer_type: LlamaTokenizer
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trust_remote_code: true
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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datasets:
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- path: Open-Orca/SlimOrca
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type: sharegpt
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conversation: chatml
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.005
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output_dir: ./slimorca-mixtral-out
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save_total_limit: 2
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hub_model_id: openaccess-ai-collective/slimorca-mixstral-8x7b
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dataloader_num_workers: 8
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dataloader_prefetch_factor: 4
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dataloader_pin_memory: true
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adapter: qlora
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lora_model_dir:
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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lora_r: 64
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lora_alpha: 32
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lora_dropout: 0.1
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lora_target_linear: true
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lora_fan_in_fan_out:
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lora_modules_to_save:
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- lm_head
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- embed_tokens
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#lora_target_modules:
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# - gate
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# - q_proj
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# - k_proj
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# - v_proj
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# - o_proj
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# - w1
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# - w2
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# - w3
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wandb_project: slimorca-mixtral
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wandb_entity: oaaic
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wandb_watch:
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wandb_name:
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 2
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.001
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adam_beta2: 0.95
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adam_epsilon: 0.00001
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max_grad_norm: 1.0
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train_on_inputs: false
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group_by_length: false
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bf16: true
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fp16: false
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tf32: true
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 100
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eval_steps: 0.05
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save_steps: 0.25
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debug:
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deepspeed: deepspeed/zero2.json
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weight_decay: 0.1
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fsdp:
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fsdp_config:
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special_tokens:
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eos_token: "<|im_end|>"
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tokens:
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- "<|im_start|>"
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:81cf5b750c5db7e8c430292756468a525455696a7015023e27c2a9bc77e7df78
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size 6011
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