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--- |
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library_name: peft |
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license: llama3.2 |
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base_model: meta-llama/Llama-3.2-1B-Instruct |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- pretraining.jsonl |
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- AiAF/SCPWiki-Archive-02-March-2025-Datasets |
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model-index: |
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- name: Pretrained-SCP-1B-QLoRA |
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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: `0.8.0.dev0` |
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```yaml |
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base_model: meta-llama/Llama-3.2-1B-Instruct |
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# Automatically upload checkpoint and final model to HF |
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hub_model_id: AiAF/Pretrained-SCP-1B-QLoRA |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: pretraining.jsonl |
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type: completion |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.1 |
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output_dir: ./outputs/qlora-out/Pretrained-SCP-1B-QLoRA |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 2048 |
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sample_packing: true |
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eval_sample_packing: true |
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pad_to_sequence_len: true |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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wandb_project: "LLM-Pretraining" |
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wandb_entity: |
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wandb_watch: "all" |
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wandb_name: "Pretrained-SCP-7B-Instruct" |
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wandb_log_model: "false" |
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gradient_accumulation_steps: 3 |
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micro_batch_size: 10 |
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num_epochs: 1 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 10 |
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evals_per_epoch: 50 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 10 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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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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# Pretrained-SCP-1B-QLoRA |
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This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on the pretraining.jsonl dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2062 |
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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: 0.0002 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 30 |
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- optimizer: Use OptimizerNames.ADAMW_BNB 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: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 3.0841 | 0.0020 | 1 | 3.0001 | |
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| 2.8276 | 0.0215 | 11 | 2.8296 | |
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| 2.3977 | 0.0431 | 22 | 2.5255 | |
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| 2.2856 | 0.0646 | 33 | 2.4384 | |
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| 2.3735 | 0.0862 | 44 | 2.4082 | |
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| 2.3645 | 0.1077 | 55 | 2.3861 | |
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| 2.1425 | 0.1292 | 66 | 2.3694 | |
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| 2.1541 | 0.1508 | 77 | 2.3545 | |
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| 2.2848 | 0.1723 | 88 | 2.3410 | |
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| 2.2334 | 0.1939 | 99 | 2.3310 | |
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| 2.1278 | 0.2154 | 110 | 2.3213 | |
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| 2.159 | 0.2369 | 121 | 2.3112 | |
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| 2.1407 | 0.2585 | 132 | 2.3006 | |
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| 1.9851 | 0.2800 | 143 | 2.2915 | |
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| 2.0319 | 0.3016 | 154 | 2.2839 | |
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| 2.2373 | 0.3231 | 165 | 2.2755 | |
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| 2.1488 | 0.3446 | 176 | 2.2684 | |
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| 2.0218 | 0.3662 | 187 | 2.2612 | |
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| 1.9256 | 0.3877 | 198 | 2.2552 | |
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| 2.0179 | 0.4093 | 209 | 2.2486 | |
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| 2.0768 | 0.4308 | 220 | 2.2448 | |
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| 2.1068 | 0.4523 | 231 | 2.2408 | |
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| 2.1343 | 0.4739 | 242 | 2.2356 | |
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| 2.2212 | 0.4954 | 253 | 2.2342 | |
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| 2.0442 | 0.5170 | 264 | 2.2302 | |
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| 2.0805 | 0.5385 | 275 | 2.2256 | |
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| 1.9695 | 0.5601 | 286 | 2.2230 | |
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| 1.8559 | 0.5816 | 297 | 2.2206 | |
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| 2.0997 | 0.6031 | 308 | 2.2185 | |
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| 2.0168 | 0.6247 | 319 | 2.2164 | |
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| 1.9304 | 0.6462 | 330 | 2.2148 | |
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| 1.9313 | 0.6678 | 341 | 2.2132 | |
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| 2.1708 | 0.6893 | 352 | 2.2119 | |
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| 2.0596 | 0.7108 | 363 | 2.2109 | |
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| 2.1944 | 0.7324 | 374 | 2.2099 | |
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| 2.0098 | 0.7539 | 385 | 2.2094 | |
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| 2.0344 | 0.7755 | 396 | 2.2087 | |
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| 2.1658 | 0.7970 | 407 | 2.2080 | |
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| 2.1188 | 0.8185 | 418 | 2.2078 | |
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| 1.879 | 0.8401 | 429 | 2.2072 | |
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| 1.9652 | 0.8616 | 440 | 2.2068 | |
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| 2.0429 | 0.8832 | 451 | 2.2066 | |
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| 2.3038 | 0.9047 | 462 | 2.2064 | |
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| 2.153 | 0.9262 | 473 | 2.2063 | |
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| 2.0543 | 0.9478 | 484 | 2.2062 | |
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| 2.0093 | 0.9693 | 495 | 2.2062 | |
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| 2.2437 | 0.9909 | 506 | 2.2062 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.49.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
