151 lines
3.2 KiB
Markdown
151 lines
3.2 KiB
Markdown
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---
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license: apache-2.0
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base_model: Qwen/Qwen2-7B
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tags:
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- generated_from_trainer
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model-index:
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- name: outputs/out
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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: `0.4.1`
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```yaml
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base_model: Qwen/Qwen2-7B
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trust_remote_code: true
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chat_template: chatml
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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: arcee-ai/MyAlee-Education-Instructions-V2
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type: sharegpt
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field_messages: messages
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- path: Crystalcareai/Orca-Reka
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type: alpaca
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dataset_prepared_path:
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val_set_size: 0
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output_dir: ./outputs/out
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sequence_len: 16384
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sample_packing: true
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eval_sample_packing: false
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pad_to_sequence_len: true
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# adapter: qlora
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# lora_model_dir:
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# lora_r: 32
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# lora_alpha: 64
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# lora_dropout: 0.05
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# lora_target_linear: true
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# lora_fan_in_fan_out:
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# wandb_project: qwen2-education
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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: 4
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micro_batch_size: 1
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num_epochs: 5
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 1e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: true
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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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: 10
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evals_per_epoch: 0
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saves_per_epoch: 1
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max_total_saves: 2
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debug:
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
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weight_decay: 0.1
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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: true
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# fsdp_use_orig_params: false
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# fsdp_cpu_ram_efficient_loading: true
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# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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# fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
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# fsdp_state_dict_type: FULL_STATE_DICT
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special_tokens:
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pad_token: "<|endoftext|>"
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eos_token: "<|im_end|>"
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```
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</details><br>
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# outputs/out
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This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) 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: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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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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- lr_scheduler_warmup_steps: 10
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- num_epochs: 5
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### Training results
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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