| --- |
| library_name: transformers |
| license: llama3.1 |
| base_model: meta-llama/Llama-3.1-8B-Instruct |
| tags: |
| - generated_from_trainer |
| datasets: |
| - tokenized_novelty_dataset_4/train_full.parquet |
| model-index: |
| - name: outputs_4/llama31-8B-liger-ds-full |
| 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: `0.12.2` |
| ```yaml |
| base_model: meta-llama/Llama-3.1-8B-Instruct |
| |
| #load_in_4bit: true |
| |
| #adapter: lora |
| #lora_r: 16 |
| #lora_alpha: 32 |
| #lora_dropout: 0.05 |
| #lora_target_modules: |
| # - q_proj |
| # - v_proj |
| # - k_proj |
| # - o_proj |
| |
| |
| plugins: |
| - axolotl.integrations.liger.LigerPlugin |
| liger_rope: true |
| liger_rms_norm: true |
| liger_glu_activation: true |
| liger_fused_linear_cross_entropy: true |
| |
| strict: false |
| |
| chat_template: llama3 |
| datasets: |
| - path: "tokenized_novelty_dataset_4/train_full.parquet" |
| type: |
| ds_type: parquet |
| |
| dataset_prepared_path: |
| val_set_size: 0.00 |
| output_dir: ./outputs_4/llama31-8B-liger-ds-full |
| |
| dataset_processes: 16 |
| |
| sequence_len: 32120 |
| sample_packing: false |
| pad_to_sequence_len: true |
| |
| gradient_accumulation_steps: 1 |
| micro_batch_size: 1 |
| num_epochs: 3 |
| optimizer: adamw_torch |
| lr_scheduler: cosine |
| learning_rate: 2e-5 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: auto |
| fp16: |
| tf32: true |
| |
| gradient_checkpointing: true |
| gradient_checkpointing_kwargs: |
| use_reentrant: false |
| early_stopping_patience: |
| resume_from_checkpoint: |
| logging_steps: 1 |
| flash_attention: true |
| |
| warmup_steps: 50 |
| evals_per_epoch: 0 |
| eval_table_size: |
| saves_per_epoch: 2 |
| save_only_model: true |
| debug: |
| deepspeed: deepspeed_configs/zero3_bf16.json |
| weight_decay: 0.0 |
| fsdp: |
| fsdp_config: |
| special_tokens: |
| pad_token: <|finetune_right_pad_id|> |
| eos_token: <|eot_id|> |
| |
| |
| ``` |
|
|
| </details><br> |
|
|
| # outputs_4/llama31-8B-liger-ds-full |
| |
| This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the tokenized_novelty_dataset_4/train_full.parquet dataset. |
| |
| ## 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: 2e-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 32 |
| - total_train_batch_size: 32 |
| - total_eval_batch_size: 32 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 50 |
| - training_steps: 2433 |
|
|
| ### Training results |
|
|
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.55.2 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
|
|
