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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ base_model: NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
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+ model-index:
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+ - name: Nous-Hermes-2-Mixtral-8x7B-SFT-Alpaca
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+ results: []
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+ ---
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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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+
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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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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
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+ model_type: MixtralForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ trust_remote_code: true
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+
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+ # hub_model_id: MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Function-Calling
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+ hub_model_id: MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Alpaca
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+ hf_use_auth_token: true
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+
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+ load_in_4bit: true
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+ strict: false
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+
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+ # datasets:
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+ # - path: Arist12/EABF-ShareGPT-Long-3.5k
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+ # type: sharegpt
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+ # conversation: chatml
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+ # datasets:
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+ # - path: hypervariance/function-calling-sharegpt
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+ # type: sharegpt
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+ # conversation: chatml
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+ datasets:
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+ - path: tatsu-lab/alpaca
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+ type: alpaca
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+
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0.1
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+ output_dir: ./qlora-out
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+
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+ # save_safetensors: true
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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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+ sequence_len: 1024
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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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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+ 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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+
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+ wandb_project:
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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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+
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+ gradient_accumulation_steps: 4
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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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+
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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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+
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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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+
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+ loss_watchdog_threshold: 5.0
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+ loss_watchdog_patience: 3
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+
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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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+ 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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+
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+ </details><br>
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+
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+ # Nous-Hermes-2-Mixtral-8x7B-SFT-Alpaca
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+
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+ This model is a fine-tuned version of [NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0276
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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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: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.3912 | 0.01 | 1 | 1.3714 |
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+ | 1.0321 | 0.25 | 45 | 1.0427 |
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+ | 1.0312 | 0.51 | 90 | 1.0327 |
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+ | 0.9917 | 0.76 | 135 | 1.0276 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.8.2
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+ - Transformers 4.38.0.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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+ "task_type": "CAUSAL_LM",
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