| | --- |
| | library_name: peft |
| | license: mit |
| | base_model: unsloth/Phi-3-mini-4k-instruct |
| | tags: |
| | - axolotl |
| | - generated_from_trainer |
| | model-index: |
| | - name: ba55cd3e-0abc-40f1-8d7b-be7e54d8b3cd |
| | 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: qlora |
| | auto_resume_from_checkpoints: true |
| | base_model: unsloth/Phi-3-mini-4k-instruct |
| | bf16: auto |
| | chat_template: llama3 |
| | dataset_prepared_path: null |
| | dataset_processes: 6 |
| | datasets: |
| | - data_files: |
| | - 27baa28e2081da37_train_data.json |
| | ds_type: json |
| | format: custom |
| | path: /workspace/input_data/27baa28e2081da37_train_data.json |
| | type: |
| | field_instruction: prompt |
| | field_output: gold_standard_solution |
| | format: '{instruction}' |
| | no_input_format: '{instruction}' |
| | system_format: '{system}' |
| | system_prompt: '' |
| | debug: null |
| | deepspeed: null |
| | early_stopping_patience: 3 |
| | eval_max_new_tokens: 128 |
| | eval_steps: 200 |
| | eval_table_size: null |
| | evals_per_epoch: null |
| | flash_attention: true |
| | fp16: false |
| | fsdp: null |
| | fsdp_config: null |
| | gradient_accumulation_steps: 4 |
| | gradient_checkpointing: true |
| | group_by_length: false |
| | hub_model_id: error577/ba55cd3e-0abc-40f1-8d7b-be7e54d8b3cd |
| | hub_repo: null |
| | hub_strategy: checkpoint |
| | hub_token: null |
| | learning_rate: 0.0002 |
| | load_in_4bit: true |
| | load_in_8bit: false |
| | local_rank: null |
| | logging_steps: 1 |
| | lora_alpha: 64 |
| | lora_dropout: 0.1 |
| | lora_fan_in_fan_out: null |
| | lora_model_dir: null |
| | lora_r: 32 |
| | lora_target_linear: true |
| | lr_scheduler: cosine |
| | max_grad_norm: 1.0 |
| | max_steps: null |
| | micro_batch_size: 2 |
| | mlflow_experiment_name: /tmp/27baa28e2081da37_train_data.json |
| | model_type: AutoModelForCausalLM |
| | num_epochs: 3 |
| | 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: 200 |
| | sequence_len: 512 |
| | strict: false |
| | tf32: false |
| | tokenizer_type: AutoTokenizer |
| | train_on_inputs: false |
| | trust_remote_code: true |
| | val_set_size: 0.005 |
| | wandb_entity: null |
| | wandb_mode: online |
| | wandb_name: 5ada3ea5-5a8e-4e04-a917-5857ffb8b096 |
| | wandb_project: Gradients-On-Demand |
| | wandb_run: your_name |
| | wandb_runid: 5ada3ea5-5a8e-4e04-a917-5857ffb8b096 |
| | warmup_steps: 30 |
| | weight_decay: 0.0 |
| | xformers_attention: null |
| | |
| | ``` |
| |
|
| | </details><br> |
| |
|
| | # ba55cd3e-0abc-40f1-8d7b-be7e54d8b3cd |
| |
|
| | This model is a fine-tuned version of [unsloth/Phi-3-mini-4k-instruct](https://huggingface.co/unsloth/Phi-3-mini-4k-instruct) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2144 |
| |
|
| | ## 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: 2 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 8 |
| | - 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: 30 |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.9665 | 0.0001 | 1 | 0.3062 | |
| | | 1.5107 | 0.0234 | 200 | 0.2194 | |
| | | 1.2022 | 0.0468 | 400 | 0.2141 | |
| | | 0.6125 | 0.0702 | 600 | 0.2148 | |
| | | 0.9861 | 0.0936 | 800 | 0.2137 | |
| | | 1.3334 | 0.1170 | 1000 | 0.2147 | |
| | | 0.7461 | 0.1404 | 1200 | 0.2137 | |
| | | 0.6805 | 0.1637 | 1400 | 0.2144 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.13.2 |
| | - Transformers 4.46.0 |
| | - Pytorch 2.5.0+cu124 |
| | - Datasets 3.0.1 |
| | - Tokenizers 0.20.1 |
