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---
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library_name: peft
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license: apache-2.0
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base_model: Qwen/Qwen2-0.5B-Instruct
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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: test-default2
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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/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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device_map: auto
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do_eval: true
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# early_stopping_patience: 5
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eval_batch_size: 4
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eval_max_new_tokens: 128
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eval_steps: 20
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eval_table_size: null
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evals_per_epoch: null
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flash_attention: true
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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: 4
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gradient_checkpointing: false
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group_by_length: true
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hub_model_id: baby-dev/test-default2
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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: 0.0002
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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: 64
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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: 32
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lora_target_linear: true
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lr_scheduler: cosine
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max_grad_norm: 1.0
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max_memory:
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0: 75GB
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max_steps: 80
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micro_batch_size: 4
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mlflow_experiment_name: /tmp/775410f20973b41e_train_data.json
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model_type: AutoModelForCausalLM
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num_epochs: 3
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optim_args:
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adam_beta1: 0.9
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adam_beta2: 0.95
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adam_epsilon: 1e-5
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optimizer: adamw_bnb_8bit
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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: 20
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save_strategy: 'no'
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saves_per_epoch: null
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sequence_len: 512
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strict: false
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tf32: true
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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: 4d2bab76-4597-405a-80aa-8803157f8fdf
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wandb_project: Gradients-On-Demand
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wandb_run: your_name
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wandb_runid: 4d2bab76-4597-405a-80aa-8803157f8fdf
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warmup_steps: 10
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weight_decay: 0.0
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xformers_attention: null
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```
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</details><br>
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# test-default2
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This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1621
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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: 0.0002
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- training_steps: 80
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 2.4891 | 0.0004 | 1 | 2.7103 |
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| 2.3198 | 0.0085 | 20 | 2.3418 |
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| 2.1863 | 0.0169 | 40 | 2.2114 |
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| 2.156 | 0.0254 | 60 | 2.1687 |
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| 2.2633 | 0.0339 | 80 | 2.1621 |
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### Framework versions
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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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---
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library_name: peft
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license: apache-2.0
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base_model: Qwen/Qwen2-0.5B-Instruct
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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: test-default2
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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/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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# test-default2
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This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1621
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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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### Framework versions
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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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