--- library_name: transformers license: apache-2.0 base_model: Qwen/Qwen2.5-Math-7B tags: - generated_from_trainer model-index: - name: axolotl-outputs/Arcee-7B-Mathy-7B-6e results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.5.0` ```yaml base_model: Qwen/Qwen2.5-Math-7B plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: true strict: false chat_template: chatml datasets: - path: arcee-ai/orcamath_evol_85k type: chat_template split: train field_messages: conversations message_field_role: from message_field_content: value - path: allenai/tulu-3-sft-personas-math type: chat_template split: train[:10%] field_messages: messages message_field_role: role message_field_content: content - path: allenai/tulu-3-sft-personas-algebra type: chat_template split: train field_messages: messages message_field_role: role message_field_content: content dataset_prepared_path: ./axolotl-datasets/math-evol-prepared val_set_size: 0.02 output_dir: ./axolotl-outputs/Arcee-7B-Mathy-7B-6e sequence_len: 4096 sample_packing: true eval_sample_packing: false pad_to_sequence_len: true wandb_project: "Arcee-Mathy-7B" wandb_entity: wandb_watch: wandb_name: wandb_log_model: gradient_accumulation_steps: 8 micro_batch_size: 4 num_epochs: 6 optimizer: adamw_torch_fused #adamw_torch_fused # if you have OOM errors you can use adamw_8bit lr_scheduler: linear learning_rate: 5e-6 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: true gradient_checkpointing_kwargs: use_reentrant: true early_stopping_patience: resume_from_checkpoint: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 50 evals_per_epoch: 1 eval_table_size: saves_per_epoch: 1 debug: deepspeed: deepspeed_configs/zero3_bf16.json weight_decay: 0.0 special_tokens: pad_token: <|endoftext|> eos_token: <|im_end|> ```

# axolotl-outputs/Arcee-7B-Mathy-7B-6e This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.5608 ## 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: 5e-06 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - total_train_batch_size: 256 - total_eval_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - num_epochs: 6 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.4101 | 0.0106 | 1 | 1.6490 | | 0.2319 | 0.9987 | 94 | 1.5007 | | 0.2234 | 1.9960 | 188 | 1.5070 | | 0.205 | 2.9920 | 282 | 1.5350 | | 0.1979 | 3.9894 | 376 | 1.5456 | | 0.1866 | 4.9867 | 470 | 1.5547 | | 0.1926 | 5.9827 | 564 | 1.5608 | ### Framework versions - Transformers 4.46.1 - Pytorch 2.3.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.3