--- base_model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated library_name: peft tags: - generated_from_trainer model-index: - name: Meta-Llama-3.1-8B-Instruct-abliterated-ICONN-1-BasicChat results: [] license: llama3.1 datasets: - Enderchef/ICONN-1-BasicChat-Data-SuperLite --- [Meta-Llama-3.1-8B-Instruct-abliterated](https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated) finetuned using the [ICONN-1-BasicChat-Data-SuperLite](https://huggingface.co/datasets/Enderchef/ICONN-1-BasicChat-Data-SuperLite) dataset as requested by [@Enderchef](https://huggingface.co/Enderchef) under https://huggingface.co/mradermacher/model_requests/discussions/918 axolotl version: `0.9.0` ```yaml base_model: /dpool/Meta-Llama-3.1-8B-Instruct-abliterated model_type: LlamaForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false datasets: - path: /apool/axolotl/0001.parquet chat_template: llama3 type: system_prompt: "" field_system: system field_instruction: input field_output: output dataset_prepared_path: val_set_size: 0.05 output_dir: ./outputs/lora-out adapter: lora lora_model_dir: sequence_len: 4096 sample_packing: false pad_to_sequence_len: true lora_r: 16 lora_alpha: 32 lora_dropout: 0.05 lora_target_linear: true gradient_accumulation_steps: 4 micro_batch_size: 2 num_epochs: 8 optimizer: adamw_torch_fused lr_scheduler: cosine learning_rate: 0.00001 bf16: auto tf32: false gradient_checkpointing: true gradient_checkpointing_kwargs: use_reentrant: true resume_from_checkpoint: logging_steps: 1 flash_attention: true warmup_steps: 10 evals_per_epoch: 4 saves_per_epoch: 1 weight_decay: 0.0 fsdp: - full_shard - auto_wrap fsdp_config: fsdp_limit_all_gathers: true fsdp_sync_module_states: true fsdp_offload_params: true fsdp_use_orig_params: false fsdp_cpu_ram_efficient_loading: true fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer fsdp_state_dict_type: FULL_STATE_DICT fsdp_sharding_strategy: FULL_SHARD special_tokens: pad_token: <|end_of_text|> ``` ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - total_eval_batch_size: 4 - 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: cosine - lr_scheduler_warmup_steps: 10 - num_epochs: 8.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.5587 | 0.0336 | 1 | 3.4337 | | 3.6702 | 0.2689 | 8 | 3.4260 | | 3.5802 | 0.5378 | 16 | 3.3161 | | 3.2421 | 0.8067 | 24 | 3.0272 | | 2.322 | 1.0672 | 32 | 2.4812 | | 1.9774 | 1.3361 | 40 | 1.8708 | | 1.5103 | 1.6050 | 48 | 1.3871 | | 1.1904 | 1.8739 | 56 | 1.0542 | | 1.0394 | 2.1345 | 64 | 0.8591 | | 0.5501 | 2.4034 | 72 | 0.6723 | | 0.2454 | 2.6723 | 80 | 0.5369 | | 0.4499 | 2.9412 | 88 | 0.4286 | | 0.2194 | 3.2017 | 96 | 0.3691 | | 0.1172 | 3.4706 | 104 | 0.2802 | | 0.0739 | 3.7395 | 112 | 0.1948 | | 0.1524 | 4.0 | 120 | 0.1457 | | 0.0444 | 4.2689 | 128 | 0.1125 | | 0.1385 | 4.5378 | 136 | 0.0759 | | 0.0591 | 4.8067 | 144 | 0.0560 | | 0.0252 | 5.0672 | 152 | 0.0460 | | 0.0066 | 5.3361 | 160 | 0.0370 | | 0.023 | 5.6050 | 168 | 0.0252 | | 0.0033 | 5.8739 | 176 | 0.0202 | | 0.0029 | 6.1345 | 184 | 0.0168 | | 0.0024 | 6.4034 | 192 | 0.0154 | | 0.0103 | 6.6723 | 200 | 0.0146 | | 0.0108 | 6.9412 | 208 | 0.0139 | | 0.0049 | 7.2017 | 216 | 0.0138 | | 0.0025 | 7.4706 | 224 | 0.0139 | | 0.0036 | 7.7395 | 232 | 0.0136 | ### Framework versions - PEFT 0.15.2 - Transformers 4.51.3 - Pytorch 2.7.0+cu128 - Datasets 3.5.0 - Tokenizers 0.21.1