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README.md CHANGED
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: HuggingFaceTB/SmolLM2-360M
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: outputs/smollm360m
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+ results: []
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+ ---
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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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+
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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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+
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+ axolotl version: `0.5.0`
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+ ```yaml
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+ base_model: HuggingFaceTB/SmolLM2-360M
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: ./dataforge
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+ type: chat_template
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+
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+ field_messages: conversations
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+ message_field_role: from
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+ message_field_content: value
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+
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+ - path: HuggingFaceTB/smol-smoltalk
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+ type: chat_template
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+
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+ field_messages: messages
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+ message_field_role: role
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+ message_field_content: content
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+
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+ chat_template: chatml
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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/smollm360m
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+
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+ # adapter: qlora
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+ # lora_model_dir:
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+
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+ sequence_len: 8192
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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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+
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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_target_linear: true
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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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+
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+ wandb_project: axolotl
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name: smollm2
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 4
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+ micro_batch_size: 4
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+ num_epochs: 2
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 1.0e-03
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: true
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+ fp16:
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+ tf32: false
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+
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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: 5
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+ xformers_attention:
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+ flash_attention: true
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+
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+ # loss_watchdog_threshold: 5.0
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+ # loss_watchdog_patience: 3
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+
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+ warmup_steps: 10
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+ evals_per_epoch: 4
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+ eval_table_size:
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+ eval_max_new_tokens: 128
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+ saves_per_epoch: 1
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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: "<|im_end|>"
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+ eos_token: "<|im_end|>"
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+ ```
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+
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+ </details><br>
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+
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+ # outputs/smollm360m
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+
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+ This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8925
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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+ - optimizer: Use adamw_bnb_8bit 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: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | No log | 0.0003 | 1 | 1.3366 |
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+ | 1.0595 | 0.2501 | 774 | 1.0840 |
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+ | 1.0194 | 0.5002 | 1548 | 1.0139 |
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+ | 1.0075 | 0.7504 | 2322 | 0.9701 |
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+ | 1.0286 | 1.0005 | 3096 | 0.9269 |
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+ | 0.7871 | 1.2506 | 3870 | 0.9111 |
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+ | 0.7481 | 1.5007 | 4644 | 0.8960 |
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+ | 0.7429 | 1.7508 | 5418 | 0.8925 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
config.json ADDED
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+ }
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