{
  "base_model": "dimasik87/07e17751-ab33-467b-b4a3-c3d1a9b3ecbe",
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    {
      "model_id": "dimasik87/07e17751-ab33-467b-b4a3-c3d1a9b3ecbe",
      "gated": "False",
      "card": "---\nlibrary_name: peft\nlicense: llama3.1\nbase_model: unsloth/Llama-3.1-Storm-8B\ntags:\n- axolotl\n- generated_from_trainer\nmodel-index:\n- name: 07e17751-ab33-467b-b4a3-c3d1a9b3ecbe\n  results: []\n---\n\n<!-- This model card has been generated automatically according to the information the Trainer had access to. You\nshould probably proofread and complete it, then remove this comment. -->\n\n[<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)\n<details><summary>See axolotl config</summary>\n\naxolotl version: `0.4.1`\n```yaml\nadapter: lora\nbase_model: unsloth/Llama-3.1-Storm-8B\nbf16: auto\nchat_template: llama3\ndataset_prepared_path: null\ndatasets:\n- data_files:\n  - c8a5ff254c4cb151_train_data.json\n  ds_type: json\n  field: synthesized text\n  path: /workspace/input_data/c8a5ff254c4cb151_train_data.json\n  type: completion\ndebug: null\ndeepspeed: null\nearly_stopping_patience: null\neval_max_new_tokens: 128\neval_table_size: null\nevals_per_epoch: 3\nflash_attention: false\nfp16: null\nfsdp: null\nfsdp_config: null\ngradient_accumulation_steps: 6\ngradient_checkpointing: true\ngroup_by_length: false\nhub_model_id: dimasik87/07e17751-ab33-467b-b4a3-c3d1a9b3ecbe\nhub_repo: null\nhub_strategy: checkpoint\nhub_token: null\nlearning_rate: 0.0001\nload_in_4bit: false\nload_in_8bit: false\nlocal_rank: null\nlogging_steps: 1\nlora_alpha: 64\nlora_dropout: 0.05\nlora_fan_in_fan_out: null\nlora_model_dir: null\nlora_r: 32\nlora_target_linear: true\nlr_scheduler: cosine\nmax_memory:\n  0: 70GiB\nmax_steps: 50\nmicro_batch_size: 4\nmlflow_experiment_name: /tmp/c8a5ff254c4cb151_train_data.json\nmodel_type: AutoModelForCausalLM\nnum_epochs: 3\noptimizer: adamw_torch\noutput_dir: miner_id_24\npad_to_sequence_len: true\nresume_from_checkpoint: null\ns2_attention: null\nsample_packing: false\nsave_steps: 25\nsave_strategy: steps\nsequence_len: 2048\nstrict: false\ntf32: false\ntokenizer_type: AutoTokenizer\ntorch_dtype: bfloat16\ntrain_on_inputs: false\ntrust_remote_code: true\nval_set_size: 0.05\nwandb_entity: null\nwandb_mode: online\nwandb_name: 07e17751-ab33-467b-b4a3-c3d1a9b3ecbe\nwandb_project: Gradients-On-Demand\nwandb_run: your_name\nwandb_runid: 07e17751-ab33-467b-b4a3-c3d1a9b3ecbe\nwarmup_steps: 10\nweight_decay: 0.01\nxformers_attention: null\n\n```\n\n</details><br>\n\n# 07e17751-ab33-467b-b4a3-c3d1a9b3ecbe\n\nThis model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset.\nIt achieves the following results on the evaluation set:\n- Loss: nan\n\n## Model description\n\nMore information needed\n\n## Intended uses & limitations\n\nMore information needed\n\n## Training and evaluation data\n\nMore information needed\n\n## Training procedure\n\n### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 0.0001\n- train_batch_size: 4\n- eval_batch_size: 4\n- seed: 42\n- gradient_accumulation_steps: 6\n- total_train_batch_size: 24\n- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments\n- lr_scheduler_type: cosine\n- lr_scheduler_warmup_steps: 10\n- training_steps: 50\n\n### Training results\n\n| Training Loss | Epoch  | Step | Validation Loss |\n|:-------------:|:------:|:----:|:---------------:|\n| 0.0           | 0.0005 | 1    | nan             |\n| 0.0           | 0.0030 | 6    | nan             |\n| 0.0           | 0.0061 | 12   | nan             |\n| 0.0           | 0.0091 | 18   | nan             |\n| 0.0           | 0.0122 | 24   | nan             |\n| 0.0           | 0.0152 | 30   | nan             |\n| 0.0           | 0.0183 | 36   | nan             |\n| 0.0           | 0.0213 | 42   | nan             |\n| 0.0           | 0.0243 | 48   | nan             |\n\n\n### Framework versions\n\n- PEFT 0.13.2\n- Transformers 4.46.0\n- Pytorch 2.5.0+cu124\n- Datasets 3.0.1\n- Tokenizers 0.20.1",
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