Update README.md
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MaziyarPanahi
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README.md
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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: MaziyarPanahi/Qwen1.5-8x7b
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model_type: Qwen2ForCausalLM
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tokenizer_type: Qwen2Tokenizer
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trust_remote_code: true
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hub_model_id: MaziyarPanahi/Qwen1.5-8x7b-v0.1
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hf_use_auth_token: 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: Crystalcareai/MoD-150k
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type: sharegpt
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dataset_prepared_path:
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val_set_size: 0.05
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output_dir: ./Qwen1.5-8x7b-v0.1-lora-out
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model_config:
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output_router_logits: true
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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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pad_to_sequence_len: true
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lora_r: 32
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lora_alpha: 16
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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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gradient_accumulation_steps: 2
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micro_batch_size: 2
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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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: 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: 10
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evals_per_epoch: 4
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eval_table_size:
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eval_max_new_tokens: 128
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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# Qwen1.5-8x7b-v0.1
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This model is a fine-tuned version of [MaziyarPanahi/Qwen1.5-8x7b](https://huggingface.co/MaziyarPanahi/Qwen1.5-8x7b) on the [Crystalcareai/MoD-150k](https://huggingface.co/datasets/Crystalcareai/MoD-150k) dataset.
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- Transformers 4.39.0.dev0
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- Pytorch 2.2.0+cu121
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- Datasets 2.17.0
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- Tokenizers 0.15.0
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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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# Qwen1.5-8x7b-v0.1
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This model is a fine-tuned version of [MaziyarPanahi/Qwen1.5-8x7b](https://huggingface.co/MaziyarPanahi/Qwen1.5-8x7b) on the [Crystalcareai/MoD-150k](https://huggingface.co/datasets/Crystalcareai/MoD-150k) dataset.
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- Transformers 4.39.0.dev0
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- Pytorch 2.2.0+cu121
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- Datasets 2.17.0
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- Tokenizers 0.15.0
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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: MaziyarPanahi/Qwen1.5-8x7b
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model_type: Qwen2ForCausalLM
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tokenizer_type: Qwen2Tokenizer
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trust_remote_code: true
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hub_model_id: MaziyarPanahi/Qwen1.5-8x7b-v0.1
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hf_use_auth_token: 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: Crystalcareai/MoD-150k
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type: sharegpt
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dataset_prepared_path:
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val_set_size: 0.05
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output_dir: ./Qwen1.5-8x7b-v0.1-lora-out
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model_config:
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output_router_logits: true
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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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pad_to_sequence_len: true
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lora_r: 32
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lora_alpha: 16
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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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gradient_accumulation_steps: 2
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micro_batch_size: 2
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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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: 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: 10
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evals_per_epoch: 4
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eval_table_size:
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eval_max_new_tokens: 128
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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