--- library_name: transformers license: other base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml tags: - generated_from_trainer model-index: - name: outputs/out results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false datasets: - path: NewEden/Gryphe-3.5-16k-Subset type: sharegpt conversation: chatml - path: NewEden/Claude-Instruct-5k type: sharegpt conversation: chatml - path: NewEden/kaloisazasedhandsomefurry type: sharegpt conversation: chatml - path: lodrick-the-lafted/NopmWritingStruct type: sharegpt conversation: chatml - path: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small type: sharegpt conversation: chatml - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned type: sharegpt conversation: chatml - path: anthracite-org/kalo-opus-instruct-22k-no-refusal type: sharegpt conversation: chatml - path: PJMixers/lodrick-the-lafted_OpusStories-ShareGPT type: sharegpt conversation: chatml - path: NewEden/Stheno-Data-filtered-8k-subset type: sharegpt conversation: chatml - path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned type: sharegpt conversation: chatml - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered type: sharegpt conversation: chatml chat_template: chatml val_set_size: 0.01 output_dir: ./outputs/out adapter: lora_r: lora_alpha: lora_dropout: lora_target_linear: sequence_len: 16384 # sequence_len: 32768 sample_packing: true eval_sample_packing: false pad_to_sequence_len: true plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: true wandb_project: HollandV2 wandb_entity: wandb_watch: wandb_name: hollandV2 wandb_log_model: gradient_accumulation_steps: 32 micro_batch_size: 1 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.00001 weight_decay: 0.05 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: true gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_ratio: 0.1 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 1 debug: deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json fsdp: fsdp_config: special_tokens: pad_token: <|finetune_right_pad_id|> ```

# outputs/out This model is a fine-tuned version of [IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml](https://huggingface.co/IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## 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: 1e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 32 - total_train_batch_size: 64 - total_eval_batch_size: 2 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 13 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.6361 | 0.0137 | 1 | nan | | 1.3697 | 0.2601 | 19 | nan | | 1.2753 | 0.5201 | 38 | nan | | 1.2662 | 0.7802 | 57 | nan | | 1.1923 | 1.0282 | 76 | nan | | 1.1571 | 1.2883 | 95 | nan | | 1.1751 | 1.5483 | 114 | nan | | 1.1485 | 1.8084 | 133 | nan | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1