| | --- |
| | base_model: Aculi/Tinyllama-2B |
| | library_name: peft |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: outputs/thinking-tiny-llama |
| | 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: `0.4.1` |
| | ```yaml |
| | base_model: Aculi/Tinyllama-2B |
| | model_type: LlamaForCausalLM |
| | tokenizer_type: LlamaTokenizer |
| | |
| | load_in_8bit: false |
| | load_in_4bit: true |
| | strict: false |
| | |
| | datasets: |
| | - path: ./datas/1.json |
| | type: alpaca |
| | - path: ./datas/2.json |
| | type: alpaca |
| | |
| | dataset_prepared_path: |
| | val_set_size: 0.05 |
| | output_dir: ./outputs/thinking-tiny-llama |
| | |
| | adapter: qlora |
| | lora_model_dir: |
| | |
| | sequence_len: 4096 |
| | sample_packing: true |
| | eval_sample_packing: false |
| | pad_to_sequence_len: true |
| | |
| | lora_r: 32 |
| | lora_alpha: 16 |
| | lora_dropout: 0.05 |
| | lora_target_modules: |
| | lora_target_linear: true |
| | lora_fan_in_fan_out: |
| | |
| | wandb_project: |
| | wandb_entity: |
| | wandb_watch: |
| | wandb_name: |
| | wandb_log_model: |
| | |
| | gradient_accumulation_steps: 4 |
| | micro_batch_size: 2 |
| | num_epochs: 4 |
| | optimizer: paged_adamw_32bit |
| | lr_scheduler: cosine |
| | learning_rate: 0.0002 |
| | |
| | train_on_inputs: false |
| | group_by_length: false |
| | bf16: auto |
| | fp16: |
| | tf32: false |
| | |
| | gradient_checkpointing: true |
| | early_stopping_patience: |
| | resume_from_checkpoint: |
| | local_rank: |
| | logging_steps: 1 |
| | xformers_attention: false |
| | flash_attention: true |
| | |
| | warmup_steps: 10 |
| | evals_per_epoch: 2 |
| | saves_per_epoch: 2 |
| | debug: |
| | deepspeed: |
| | weight_decay: 0.0 |
| | fsdp: |
| | fsdp_config: |
| | special_tokens: |
| | ``` |
| |
|
| | </details><br> |
| |
|
| | # outputs/thinking-tiny-llama |
| |
|
| | This model is a fine-tuned version of [Aculi/Tinyllama-2B](https://huggingface.co/Aculi/Tinyllama-2B) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.0222 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 8 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 10 |
| | - num_epochs: 4 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 1.5625 | 0.0013 | 1 | 1.5692 | |
| | | 1.1161 | 0.5002 | 400 | 1.0995 | |
| | | 1.0509 | 1.0003 | 800 | 1.0633 | |
| | | 1.0665 | 1.4867 | 1200 | 1.0422 | |
| | | 1.012 | 1.9869 | 1600 | 1.0287 | |
| | | 1.0124 | 2.4733 | 2000 | 1.0250 | |
| | | 0.8544 | 2.9734 | 2400 | 1.0212 | |
| | | 0.9435 | 3.4605 | 2800 | 1.0222 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.11.1 |
| | - Transformers 4.43.1 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
