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--- |
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license: other |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: NousResearch/Meta-Llama-3-70B |
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model-index: |
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- name: 2-qlora-out-l3-10 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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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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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: NousResearch/Meta-Llama-3-70B |
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model_type: LlamaForCausalLM |
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tokenizer_type: PreTrainedTokenizerFast |
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#overrides_of_model_config: |
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# rope_scaling: |
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# type: linear |
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# factor: 4 |
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special_tokens: |
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pad_token: "<|end_of_text|>" |
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gptq: false |
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gptq_disable_exllama: 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: /workspace/axolotl/output.jsonl |
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ds_type: json |
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type: completion |
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data_files: |
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- /workspace/axolotl/output.jsonl |
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output_dir: ./2-qlora-out-l3-10 |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 2048 |
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sample_packing: true |
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eval_sample_packing: true |
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pad_to_sequence_len: true |
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lora_r: 32 |
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lora_alpha: 90 |
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lora_dropout: 0.10 |
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lora_target_linear: true |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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peft_use_dora: true |
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wandb_project: kalomaze-model |
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wandb_entity: |
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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: 2 |
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num_epochs: 4 |
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# optimizer: paged_adamw_8bit |
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# optimizer: adamw_bnb_8bit |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000015 |
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cosine_min_lr_ratio: 0.2 |
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max_grad_norm: 1.0 |
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train_on_inputs: true |
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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: false |
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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: 0 |
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saves_per_epoch: 2 |
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save_total_limit: 7 |
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debug: |
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weight_decay: 0.0 |
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# fsdp: |
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# - full_shard |
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# - auto_wrap |
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# fsdp_config: |
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# fsdp_limit_all_gathers: true |
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# fsdp_sync_module_states: true |
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# fsdp_offload_params: false |
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# fsdp_use_orig_params: false |
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# fsdp_cpu_ram_efficient_loading: false |
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# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP |
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# fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer |
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# fsdp_state_dict_type: FULL_STATE_DICT |
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seed: 246 |
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``` |
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</details><br> |
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# 2-qlora-out-l3-10 |
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This model is a fine-tuned version of [NousResearch/Meta-Llama-3-70B](https://huggingface.co/NousResearch/Meta-Llama-3-70B) on the None dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1.5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 246 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 4 |
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### Training results |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
