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--- |
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library_name: transformers |
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license: llama3.2 |
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base_model: meta-llama/Llama-3.2-3B-Instruct |
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tags: |
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- generated_from_trainer |
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datasets: |
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- shuffled_output.json |
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model-index: |
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- name: models/llama_wm_v3 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.5.3.dev44+g5bef1906` |
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```yaml |
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base_model: meta-llama/Llama-3.2-3B-Instruct |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_glu_activation: true |
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liger_layer_norm: true |
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liger_fused_linear_cross_entropy: true |
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datasets: |
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- path: shuffled_output.json |
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type: input_output |
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dataset_prepared_path: last_run_prepared |
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dataset_exact_deduplication: false |
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sequence_length: 131072 |
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pad_to_sequence_len: true |
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output_dir: ./models/llama_wm_v3 |
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wandb_project: agent-v0 |
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wandb_name: llama-3b_wm_v3 |
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train_on_inputs: false |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 4 |
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num_epochs: 1 |
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optimizer: adamw_torch |
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learning_rate: 2e-5 |
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xformers_attention: |
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flash_attention: true |
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logging_steps: 5 |
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warmup_steps: 10 |
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saves_per_epoch: 1 |
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weight_decay: 0.0 |
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deepspeed: axolotl/deepspeed_configs/zero3_bf16_cpuoffload_all.json |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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# models/llama_wm_v3 |
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This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the shuffled_output.json dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 1 |
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### Training results |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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