--- tags: - generated_from_trainer model-index: - name: lora-out results: [] --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) # lora-out This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.2973 ## 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: 0.00065 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - lr_scheduler_warmup_steps: 10 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.5404 | 0.03 | 20 | 1.2764 | | 1.4523 | 0.06 | 40 | 1.2571 | | 1.5608 | 0.09 | 60 | 1.2465 | | 1.5921 | 0.12 | 80 | 1.2575 | | 1.6043 | 0.15 | 100 | 1.2432 | | 1.5496 | 0.18 | 120 | 1.2504 | | 1.348 | 0.21 | 140 | 1.2452 | | 1.4638 | 0.24 | 160 | 1.2661 | | 1.5733 | 0.27 | 180 | 1.2548 | | 1.5397 | 0.3 | 200 | 1.2674 | | 1.6154 | 0.33 | 220 | 1.2626 | | 1.5058 | 0.36 | 240 | 1.2672 | | 1.3974 | 0.4 | 260 | 1.2659 | | 1.6654 | 0.43 | 280 | 1.2648 | | 1.8051 | 0.46 | 300 | 1.2585 | | 1.7487 | 0.49 | 320 | 1.2736 | | 1.3612 | 0.52 | 340 | 1.2717 | | 1.5048 | 0.55 | 360 | 1.2809 | | 1.7134 | 0.58 | 380 | 1.2885 | | 1.5524 | 0.61 | 400 | 1.2805 | | 1.3705 | 0.64 | 420 | 1.2860 | | 1.4335 | 0.67 | 440 | 1.2896 | | 1.3642 | 0.7 | 460 | 1.2911 | | 1.6546 | 0.73 | 480 | 1.2888 | | 1.5345 | 0.76 | 500 | 1.2973 | | 1.5968 | 0.79 | 520 | 1.2885 | | 1.5694 | 0.82 | 540 | 1.2939 | | 1.5474 | 0.85 | 560 | 1.2892 | | 1.6981 | 0.88 | 580 | 1.2949 | | 1.5451 | 0.91 | 600 | 1.2886 | | 1.5845 | 0.94 | 620 | 1.2941 | | 1.5143 | 0.97 | 640 | 1.2973 | ### Framework versions - Transformers 4.34.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.0