Instructions to use devkyle/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use devkyle/test with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| base_model: openai/whisper-tiny | |
| library_name: peft | |
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: test | |
| 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. --> | |
| # test | |
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.2527 | |
| ## 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: 0.0001 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 50 | |
| - training_steps: 2000 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | 2.183 | 2.5 | 250 | 1.8650 | | |
| | 1.5663 | 5.0 | 500 | 1.5657 | | |
| | 1.4027 | 7.5 | 750 | 1.4221 | | |
| | 1.2577 | 10.0 | 1000 | 1.3457 | | |
| | 1.2005 | 12.5 | 1250 | 1.3022 | | |
| | 1.1409 | 15.0 | 1500 | 1.2743 | | |
| | 1.1152 | 17.5 | 1750 | 1.2585 | | |
| | 1.0965 | 20.0 | 2000 | 1.2527 | | |
| ### Framework versions | |
| - PEFT 0.13.1.dev0 | |
| - Transformers 4.44.2 | |
| - Pytorch 2.4.1+cu121 | |
| - Datasets 3.0.1 | |
| - Tokenizers 0.19.1 |