--- library_name: transformers base_model: Emm9625/Llama-3.2-1B-chatml tags: - axolotl - generated_from_trainer datasets: - Emm9625/textwork-00-dedupe-0.75 - Emm9625/textwork-00-dedupe-0.75 - Emm9625/textwork-00-dedupe-0.75 model-index: - name: tw-1b-dedupe-0.75-overfit results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<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) <details><summary>See axolotl config</summary> axolotl version: `0.6.0` ```yaml # Original base model config # base_model: Dans-DiscountModels/Meta-Llama-3.2-3B-ChatML # Using smaller model instead base_model: Emm9625/Llama-3.2-1B-chatml # Original tokenizer config # tokenizer_config: Dans-DiscountModels/Meta-Llama-3.2-3B-ChatML # Using matching tokenizer for smaller model tokenizer_config: Emm9625/Llama-3.2-1B-chatml # Model loading configuration load_in_8bit: false load_in_4bit: false strict: false # Chat template configuration chat_template: chatml # Dataset configuration datasets: - path: Emm9625/textwork-00-dedupe-0.75 name: smol-constraints split: train type: chat_template field_messages: messages message_field_role: role message_field_content: content train_on_eos: turn # shards: 2 # shard_idx: 0 - path: Emm9625/textwork-00-dedupe-0.75 name: smol-rewrite split: train type: chat_template field_messages: messages message_field_role: role message_field_content: content train_on_eos: turn # shards: 2 # shard_idx: 0 - path: Emm9625/textwork-00-dedupe-0.75 name: smol-summarize split: train type: chat_template field_messages: messages message_field_role: role message_field_content: content train_on_eos: turn # shards: 2 # shard_idx: 0 test_datasets: - path: Emm9625/textwork-00-dedupe-0.75 name: smol-constraints split: test type: chat_template field_messages: messages message_field_role: role message_field_content: content train_on_eos: turn shards: 5 shard_idx: 0 - path: Emm9625/textwork-00-dedupe-0.75 name: smol-rewrite split: test type: chat_template field_messages: messages message_field_role: role message_field_content: content train_on_eos: turn shards: 5 shard_idx: 0 - path: Emm9625/textwork-00-dedupe-0.75 name: smol-summarize split: test type: chat_template field_messages: messages message_field_role: role message_field_content: content train_on_eos: turn shards: 5 shard_idx: 0 dataset_prepared_path: /notebooks/last_run_prepared output_dir: /tmp/meow/ hub_model_id: Emm9625/tw-1b-dedupe-0.75-overfit hub_strategy: checkpoint # Whether to use hf `use_auth_token` for loading datasets. Useful for fetching private datasets # Required to be true when used in combination with `push_dataset_to_hub` hf_use_auth_token: true # Model configuration sequence_len: 4096 sample_packing: true eval_sample_packing: true pad_to_sequence_len: true adapter: lora_model_dir: lora_r: 16 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: lora_target_modules: - gate_proj - down_proj - up_proj - q_proj - v_proj - k_proj - o_proj # Unsloth optimizations unsloth_cross_entropy_loss: true unsloth_rms_norm: true unsloth_rope: true #Lora Optimizations # unsloth_lora_mlp: true # unsloth_lora_qkv: true # unsloth_lora_o: true # Training configuration gradient_accumulation_steps: 1 micro_batch_size: 8 num_epochs: 1 optimizer: adamw_8bit lr_scheduler: cosine learning_rate: 2e-5 torch_compile: auto train_on_inputs: false group_by_length: false bf16: true gradient_checkpointing: true flash_attention: true # Training monitoring loss_watchdog_threshold: 5.0 loss_watchdog_patience: 3 warmup_ratio: 0.10 weight_decay: 0.00 saves_per_epoch: 1 evals_per_epoch: 5 save_safetensors: true wandb_project: textwork-00-dedupe logging_steps: 1 # Special tokens configuration special_tokens: eos_token: "<|im_end|>" bos_token: "<|im_start|>" fsdp: fsdp_config: ``` </details><br> # tw-1b-dedupe-0.75-overfit This model is a fine-tuned version of [Emm9625/Llama-3.2-1B-chatml](https://huggingface.co/Emm9625/Llama-3.2-1B-chatml) on the Emm9625/textwork-00-dedupe-0.75, the Emm9625/textwork-00-dedupe-0.75 and the Emm9625/textwork-00-dedupe-0.75 datasets. It achieves the following results on the evaluation set: - Loss: 0.7782 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 71 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.3266 | 0.0014 | 1 | 1.3293 | | 0.8621 | 0.2006 | 144 | 0.8430 | | 0.783 | 0.4011 | 288 | 0.8020 | | 0.7862 | 0.6017 | 432 | 0.7834 | | 0.7868 | 0.8022 | 576 | 0.7782 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0