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  2. adapter_model.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: NousResearch/Yarn-Llama-2-13b-128k
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ model-index:
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+ - name: f34d5de7-5900-4cac-9129-69fb41d0db86
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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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: NousResearch/Yarn-Llama-2-13b-128k
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+ bf16: true
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+ chat_template: llama3
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+ datasets:
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+ - data_files:
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+ - 955bd35488d15e31_train_data.json
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+ ds_type: json
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+ field: title
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+ path: /workspace/input_data/955bd35488d15e31_train_data.json
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+ type: completion
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+ debug: null
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+ deepspeed: null
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+ early_stopping_patience: null
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+ eval_max_new_tokens: 128
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+ eval_table_size: null
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+ evals_per_epoch: 4
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+ flash_attention: false
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+ fp16: false
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+ fsdp: null
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+ fsdp_config: null
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+ gradient_accumulation_steps: 2
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+ gradient_checkpointing: true
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+ group_by_length: false
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+ hub_model_id: lesso04/f34d5de7-5900-4cac-9129-69fb41d0db86
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+ hub_repo: null
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+ hub_strategy: checkpoint
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+ hub_token: null
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+ learning_rate: 0.0001
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+ load_in_4bit: false
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+ load_in_8bit: false
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+ local_rank: null
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+ logging_steps: 1
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+ lora_alpha: 32
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+ lora_dropout: 0.05
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+ lora_fan_in_fan_out: null
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+ lora_model_dir: null
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+ lora_r: 16
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+ lora_target_linear: true
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+ lr_scheduler: cosine
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+ max_memory:
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+ 0: 77GiB
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+ max_steps: 100
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+ micro_batch_size: 8
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+ mlflow_experiment_name: /tmp/955bd35488d15e31_train_data.json
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 3
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+ optimizer: adamw_torch
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+ output_dir: miner_id_24
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+ pad_to_sequence_len: true
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+ resume_from_checkpoint: null
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+ s2_attention: null
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+ sample_packing: false
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+ save_steps: 25
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+ save_strategy: steps
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+ sequence_len: 1024
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+ strict: false
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+ tf32: false
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+ tokenizer_type: AutoTokenizer
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+ train_on_inputs: false
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+ trust_remote_code: true
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+ val_set_size: 0.05
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+ wandb_entity: null
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+ wandb_mode: online
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+ wandb_name: f34d5de7-5900-4cac-9129-69fb41d0db86
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+ wandb_project: Gradients-On-Demand
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+ wandb_run: your_name
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+ wandb_runid: f34d5de7-5900-4cac-9129-69fb41d0db86
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+ warmup_steps: 10
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+ weight_decay: 0.01
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+ xformers_attention: false
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+
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+ ```
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+
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+ </details><br>
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+
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+ # f34d5de7-5900-4cac-9129-69fb41d0db86
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+
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+ This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-13b-128k](https://huggingface.co/NousResearch/Yarn-Llama-2-13b-128k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1933
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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: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 10
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+ - training_steps: 100
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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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+ | 7.2804 | 0.0001 | 1 | 3.6915 |
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+ | 6.6761 | 0.0007 | 9 | 3.1253 |
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+ | 4.9393 | 0.0013 | 18 | 2.5066 |
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+ | 4.6914 | 0.0020 | 27 | 2.3536 |
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+ | 4.6689 | 0.0027 | 36 | 2.2815 |
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+ | 4.5006 | 0.0033 | 45 | 2.2529 |
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+ | 4.5399 | 0.0040 | 54 | 2.2302 |
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+ | 4.2416 | 0.0047 | 63 | 2.2146 |
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+ | 4.1861 | 0.0054 | 72 | 2.2027 |
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+ | 4.1997 | 0.0060 | 81 | 2.1964 |
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+ | 4.4412 | 0.0067 | 90 | 2.1938 |
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+ | 4.3099 | 0.0074 | 99 | 2.1933 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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