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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- axolotl |
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- generated_from_trainer |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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model-index: |
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- name: hc-tinyllama-alpaca |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: imdb_1k_alpaca.jsonl |
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type: alpaca |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.05 |
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output_dir: ./outputs/qlora-out |
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hub_model_id: satish860/hc-tinyllama-alpaca |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 4096 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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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_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 4 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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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: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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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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``` |
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</details><br> |
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# hc-tinyllama-alpaca |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0225 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 8.0151 | 0.0851 | 1 | 7.9045 | |
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| 7.967 | 0.2553 | 3 | 7.7350 | |
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| 6.5633 | 0.5106 | 6 | 4.8012 | |
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| 1.5838 | 0.7660 | 9 | 0.7756 | |
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| 0.2319 | 1.0213 | 12 | 0.1592 | |
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| 0.0669 | 1.2340 | 15 | 0.0973 | |
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| 0.0344 | 1.4894 | 18 | 0.0453 | |
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| 0.1146 | 1.7447 | 21 | 0.0754 | |
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| 0.0896 | 2.0 | 24 | 0.0517 | |
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| 0.0293 | 2.2340 | 27 | 0.0486 | |
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| 0.0378 | 2.4894 | 30 | 0.0566 | |
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| 0.0523 | 2.7447 | 33 | 0.0270 | |
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| 0.0886 | 3.0 | 36 | 0.0226 | |
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| 0.0504 | 3.2128 | 39 | 0.0232 | |
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| 0.089 | 3.4681 | 42 | 0.0225 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
