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license: apache-2.0 |
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--- |
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# Mistral-7B-code-16k-qlora |
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I'm excited to announce the release of a new model called Mistral-7B-code-16k-qlora. This small and fast model shows a lot of promise for supporting coding or acting as a copilot. I'm currently looking for people to help me test it out! |
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## Additional Information |
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This model was trained on 3x RTX 3090 in my homelab, using around 65kWh for approximately 23 cents, which is equivalent to around $15 for electricity. |
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## Prompt template: Alpaca |
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``` |
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Below is an instruction that describes a task. Write a response that appropriately completes the request. |
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### Instruction: |
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{prompt} |
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### Response: |
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``` |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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## Settings: |
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``` |
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base_model: mistralai/Mistral-7B-Instruct-v0.1 |
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base_model_config: mistralai/Mistral-7B-Instruct-v0.1 |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: 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: nickrosh/Evol-Instruct-Code-80k-v1 |
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type: oasst |
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dataset_prepared_path: |
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val_set_size: 0.01 |
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output_dir: ./Mistral-7B-Evol-Instruct-16k-test11 |
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adapter: qlora |
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lora_model_dir: |
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# 16384 8192 4096 2048 |
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sequence_len: 16384 |
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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_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: mistral-code |
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wandb_entity: |
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wandb_watch: |
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wandb_run_id: |
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wandb_log_model: |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 1 |
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num_epochs: 8 |
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optimizer: paged_adamw_32bit |
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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: 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: 10 |
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eval_steps: 20 |
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save_steps: |
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debug: |
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# deepspeed: |
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deepspeed: deepspeed/zero2.json |
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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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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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Check my other projects: |
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https://github.com/Nondzu/LlamaTor |
