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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: unsloth/SmolLM-360M |
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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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- argilla/databricks-dolly-15k-curated-en |
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model-index: |
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- name: SmolLM-360M |
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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: `0.6.0` |
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```yaml |
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base_model: unsloth/SmolLM-360M |
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batch_size: 92 |
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bf16: true |
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chat_template: tokenizer_default_fallback_alpaca |
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datasets: |
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- format: custom |
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path: argilla/databricks-dolly-15k-curated-en |
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type: |
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field_input: original-instruction |
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field_instruction: original-instruction |
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field_output: original-response |
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format: '{instruction} {input}' |
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no_input_format: '{instruction}' |
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system_format: '{system}' |
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system_prompt: '' |
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device_map: auto |
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eval_sample_packing: false |
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eval_steps: 20 |
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flash_attention: true |
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gradient_checkpointing: true |
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group_by_length: true |
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hub_model_id: SystemAdmin123/SmolLM-360M |
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hub_strategy: checkpoint |
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learning_rate: 0.0002 |
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logging_steps: 10 |
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lr_scheduler: cosine |
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max_steps: 10000 |
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micro_batch_size: 23 |
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model_type: AutoModelForCausalLM |
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num_epochs: 100 |
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optimizer: adamw_bnb_8bit |
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output_dir: /root/.sn56/axolotl/tmp/SmolLM-360M |
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pad_to_sequence_len: true |
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resize_token_embeddings_to_32x: false |
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sample_packing: true |
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save_steps: 20 |
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save_total_limit: 1 |
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sequence_len: 2048 |
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tokenizer_type: GPT2TokenizerFast |
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torch_dtype: bf16 |
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training_args_kwargs: |
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hub_private_repo: true |
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trust_remote_code: true |
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val_set_size: 0.1 |
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wandb_entity: '' |
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wandb_mode: online |
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wandb_name: unsloth/SmolLM-360M-argilla/databricks-dolly-15k-curated-en |
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wandb_project: Gradients-On-Demand |
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wandb_run: your_name |
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wandb_runid: default |
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warmup_ratio: 0.05 |
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``` |
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</details><br> |
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# SmolLM-360M |
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This model is a fine-tuned version of [unsloth/SmolLM-360M](https://huggingface.co/unsloth/SmolLM-360M) on the argilla/databricks-dolly-15k-curated-en dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0673 |
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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: 23 |
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- eval_batch_size: 23 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 92 |
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- total_eval_batch_size: 92 |
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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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- training_steps: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.125 | 1 | 2.5584 | |
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| 2.2406 | 2.5 | 20 | 2.1562 | |
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| 2.136 | 5.0 | 40 | 2.0829 | |
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| 2.0938 | 7.5 | 60 | 2.0711 | |
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| 2.0632 | 10.0 | 80 | 2.0679 | |
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| 2.0298 | 12.5 | 100 | 2.0621 | |
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| 2.0168 | 15.0 | 120 | 2.0567 | |
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| 2.0188 | 17.5 | 140 | 2.0686 | |
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| 2.0108 | 20.0 | 160 | 2.0701 | |
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| 2.0169 | 22.5 | 180 | 2.0683 | |
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| 2.0109 | 25.0 | 200 | 2.0673 | |
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### Framework versions |
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- Transformers 4.48.1 |
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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 |
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