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--- |
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base_model: Trisert/tinyllama-alpaca |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: outputs/qlora-out-context |
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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: `0.4.1` |
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```yaml |
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adapter: qlora |
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base_model: Trisert/tinyllama-alpaca |
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bf16: false |
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dataset_prepared_path: null |
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datasets: |
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- ds_tipe: json |
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path: /content/pubmed_continual_pretraning_dataset.jsonl |
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type: completion |
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debug: null |
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deepspeed: null |
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early_stopping_patience: null |
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eval_sample_packing: false |
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evals_per_epoch: 4 |
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flash_attention: false |
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fp16: null |
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fsdp: null |
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fsdp_config: null |
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gradient_accumulation_steps: 4 |
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gradient_checkpointing: true |
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group_by_length: false |
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learning_rate: 0.0002 |
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load_in_4bit: true |
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load_in_8bit: false |
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local_rank: null |
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logging_steps: 1 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_fan_in_fan_out: null |
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lora_model_dir: null |
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lora_r: 32 |
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lora_target_linear: true |
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lora_target_modules: null |
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lr_scheduler: cosine |
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micro_batch_size: 8 |
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model_type: AutoModelForCausalLM |
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num_epochs: 4 |
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optimizer: paged_adamw_32bit |
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output_dir: ./outputs/qlora-out-context |
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pad_to_sequence_len: false |
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resume_from_checkpoint: null |
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sample_packing: false |
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saves_per_epoch: 1 |
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sequence_len: 4096 |
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special_tokens: null |
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strict: false |
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tf32: false |
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tokenizer_type: AutoTokenizer |
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train_on_inputs: false |
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val_set_size: 0.05 |
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wandb_entity: null |
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wandb_log_model: null |
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wandb_name: null |
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wandb_project: null |
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wandb_watch: null |
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warmup_steps: 10 |
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weight_decay: 0.0 |
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xformers_attention: null |
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``` |
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</details><br> |
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# outputs/qlora-out-context |
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This model is a fine-tuned version of [Trisert/tinyllama-alpaca](https://huggingface.co/Trisert/tinyllama-alpaca) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8030 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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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| 2.6905 | 0.0336 | 1 | 2.7292 | |
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| 2.4725 | 0.2689 | 8 | 2.3972 | |
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| 1.9891 | 0.5378 | 16 | 2.0718 | |
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| 1.8345 | 0.8067 | 24 | 1.9329 | |
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| 1.8088 | 1.0756 | 32 | 1.8730 | |
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| 1.8183 | 1.3445 | 40 | 1.8430 | |
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| 1.8004 | 1.6134 | 48 | 1.8263 | |
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| 1.7674 | 1.8824 | 56 | 1.8167 | |
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| 1.7164 | 2.1513 | 64 | 1.8104 | |
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| 1.6525 | 2.4202 | 72 | 1.8069 | |
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| 1.7917 | 2.6891 | 80 | 1.8053 | |
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| 1.8022 | 2.9580 | 88 | 1.8037 | |
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| 1.6917 | 3.2269 | 96 | 1.8032 | |
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| 1.765 | 3.4958 | 104 | 1.8030 | |
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| 1.6784 | 3.7647 | 112 | 1.8030 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
