| | --- |
| | library_name: peft |
| | license: bigcode-openrail-m |
| | base_model: bigcode/starcoder2-3b |
| | tags: |
| | - axolotl |
| | - generated_from_trainer |
| | model-index: |
| | - name: 26f8aadc-4bc8-47ef-bc2b-e6fd3debfaa0 |
| | 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: bigcode/starcoder2-3b |
| | bf16: true |
| | chat_template: llama3 |
| | dataset_prepared_path: null |
| | datasets: |
| | - data_files: |
| | - 1f363d38b0a18fae_train_data.json |
| | ds_type: json |
| | format: custom |
| | path: /workspace/input_data/1f363d38b0a18fae_train_data.json |
| | type: |
| | field_instruction: instruction |
| | field_output: output |
| | format: '{instruction}' |
| | no_input_format: '{instruction}' |
| | system_format: '{system}' |
| | system_prompt: '' |
| | debug: null |
| | deepspeed: null |
| | device_map: auto |
| | do_eval: true |
| | early_stopping_patience: 5 |
| | eval_batch_size: 4 |
| | eval_max_new_tokens: 128 |
| | eval_steps: 50 |
| | 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: true |
| | hub_model_id: abaddon182/26f8aadc-4bc8-47ef-bc2b-e6fd3debfaa0 |
| | hub_repo: null |
| | hub_strategy: checkpoint |
| | hub_token: null |
| | learning_rate: 0.0001 |
| | load_in_4bit: false |
| | load_in_8bit: false |
| | local_rank: null |
| | logging_steps: 1 |
| | lora_alpha: 128 |
| | lora_dropout: 0.05 |
| | lora_fan_in_fan_out: null |
| | lora_model_dir: null |
| | lora_r: 64 |
| | lora_target_linear: true |
| | lr_scheduler: cosine |
| | max_grad_norm: 1.0 |
| | max_memory: |
| | 0: 75GB |
| | max_steps: 200 |
| | micro_batch_size: 8 |
| | mlflow_experiment_name: /tmp/1f363d38b0a18fae_train_data.json |
| | model_type: AutoModelForCausalLM |
| | num_epochs: 3 |
| | optim_args: |
| | adam_beta1: 0.9 |
| | adam_beta2: 0.95 |
| | adam_epsilon: 1e-5 |
| | 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: 50 |
| | saves_per_epoch: null |
| | sequence_len: 1024 |
| | special_tokens: |
| | pad_token: <|endoftext|> |
| | strict: false |
| | tf32: true |
| | tokenizer_type: AutoTokenizer |
| | train_on_inputs: false |
| | trust_remote_code: true |
| | val_set_size: 0.05 |
| | wandb_entity: null |
| | wandb_mode: online |
| | wandb_name: 11d6d6d8-0f3b-4480-adc8-58ddc86a0ed7 |
| | wandb_project: Gradients-On-Demand |
| | wandb_run: your_name |
| | wandb_runid: 11d6d6d8-0f3b-4480-adc8-58ddc86a0ed7 |
| | warmup_steps: 10 |
| | weight_decay: 0.0 |
| | xformers_attention: null |
| | |
| | ``` |
| |
|
| | </details><br> |
| |
|
| | # 26f8aadc-4bc8-47ef-bc2b-e6fd3debfaa0 |
| |
|
| | This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.4372 |
| |
|
| | ## 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: 0.0001 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - 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 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 10 |
| | - training_steps: 200 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 13.3816 | 0.0012 | 1 | 1.7327 | |
| | | 14.1459 | 0.0587 | 50 | 1.6148 | |
| | | 9.0356 | 0.1173 | 100 | 1.5398 | |
| | | 9.0892 | 0.1760 | 150 | 1.4641 | |
| | | 10.607 | 0.2346 | 200 | 1.4372 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.13.2 |
| | - Transformers 4.46.0 |
| | - Pytorch 2.5.0+cu124 |
| | - Datasets 3.0.1 |
| | - Tokenizers 0.20.1 |
