| license: apache-2.0 | |
| base_model: openai/whisper-large-v3 | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: whisper-large-v3-quantized | |
| 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. --> | |
| # whisper-large-v3-quantized | |
| This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - eval_loss: 1.1612 | |
| - eval_wer: 0.5591 | |
| - eval_runtime: 676.1374 | |
| - eval_samples_per_second: 0.602 | |
| - eval_steps_per_second: 0.075 | |
| - epoch: 0.4917 | |
| - step: 800 | |
| ## 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: 1e-05 | |
| - train_batch_size: 1 | |
| - 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: 500 | |
| - training_steps: 1000 | |
| - mixed_precision_training: Native AMP | |
| ### Framework versions | |
| - Transformers 4.43.3 | |
| - Pytorch 2.4.0+cu121 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 | |