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README.md

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----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-0.5B
-tags:
-- axolotl
-- generated_from_trainer
-model-index:
-- name: b146a7bd-c805-4b7c-be83-d2962b888655
-  results: []
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-[<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)
-<details><summary>See axolotl config</summary>
-
-axolotl version: `0.4.1`
-```yaml
-adapter: lora
-base_model: Qwen/Qwen2.5-0.5B
-bf16: auto
-chat_template: llama3
-dataset_prepared_path: null
-datasets:
-- data_files:
-  - d0d00b26ed506bf7_train_data.json
-  ds_type: json
-  format: custom
-  path: /workspace/input_data/d0d00b26ed506bf7_train_data.json
-  type:
-    field_input: gt_cot
-    field_instruction: question
-    field_output: solution
-    format: '{instruction} {input}'
-    no_input_format: '{instruction}'
-    system_format: '{system}'
-    system_prompt: ''
-debug: null
-deepspeed: null
-device: cuda
-early_stopping_patience: 1
-eval_max_new_tokens: 128
-eval_steps: 5
-eval_table_size: null
-evals_per_epoch: null
-flash_attention: false
-fp16: null
-gradient_accumulation_steps: 4
-gradient_checkpointing: true
-gradient_clipping: 1.0
-group_by_length: true
-hub_model_id: dimasik2987/b146a7bd-c805-4b7c-be83-d2962b888655
-hub_repo: null
-hub_strategy: end
-hub_token: null
-learning_rate: 0.0002
-load_in_4bit: false
-load_in_8bit: true
-local_rank: null
-logging_steps: 3
-lora_alpha: 16
-lora_dropout: 0.05
-lora_fan_in_fan_out: null
-lora_model_dir: null
-lora_r: 8
-lora_target_linear: true
-lr_scheduler: cosine
-max_memory:
-  0: 79GiB
-max_steps: 30
-micro_batch_size: 4
-mlflow_experiment_name: /tmp/d0d00b26ed506bf7_train_data.json
-model_type: AutoModelForCausalLM
-num_epochs: 1
-optimizer: adamw_bnb_8bit
-output_dir: miner_id_24
-pad_to_sequence_len: true
-resume_from_checkpoint: null
-s2_attention: null
-sample_packing: false
-save_steps: 10
-sequence_len: 1024
-strict: false
-tf32: false
-tokenizer_type: AutoTokenizer
-train_on_inputs: true
-trust_remote_code: true
-val_set_size: 0.05
-wandb_entity: null
-wandb_mode: online
-wandb_name: 4462f74d-6051-4a29-a50f-b489f3072fb6
-wandb_project: Gradients-On-Demand
-wandb_run: your_name
-wandb_runid: 4462f74d-6051-4a29-a50f-b489f3072fb6
-warmup_steps: 5
-weight_decay: 0.001
-xformers_attention: true
-
-```
-
-</details><br>
-
-# b146a7bd-c805-4b7c-be83-d2962b888655
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.3973
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0002
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
-- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 5
-- training_steps: 30
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| No log        | 0.0001 | 1    | 0.4918          |
-| 0.3168        | 0.0004 | 5    | 0.4664          |
-| 0.324         | 0.0008 | 10   | 0.4263          |
-| 0.3947        | 0.0012 | 15   | 0.4092          |
-| 0.3807        | 0.0016 | 20   | 0.4004          |
-| 0.3896        | 0.0020 | 25   | 0.3979          |
-| 0.3948        | 0.0024 | 30   | 0.3973          |
-
-
-### Framework versions
-
-- PEFT 0.13.2
-- Transformers 4.46.0
-- Pytorch 2.5.0+cu124
-- Datasets 3.0.1
-- Tokenizers 0.20.1