| language: | |
| - ms | |
| license: apache-2.0 | |
| tags: | |
| - whisper-event | |
| - incomplete | |
| - generated_from_trainer | |
| datasets: | |
| - google/fleurs | |
| model-index: | |
| - name: Whisper Small MS - FLEURS | |
| 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 Small MS - FLEURS | |
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the FLEURS dataset. | |
| It achieves the following results on the evaluation set: | |
| - eval_loss: 0.3324 | |
| - eval_wer: 15.6453 | |
| - eval_runtime: 347.6066 | |
| - eval_samples_per_second: 2.155 | |
| - eval_steps_per_second: 0.27 | |
| - epoch: 10.75 | |
| - step: 1000 | |
| ## 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: 4 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 8 | |
| - total_train_batch_size: 32 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - training_steps: 5000 | |
| - mixed_precision_training: Native AMP | |
| ### Framework versions | |
| - Transformers 4.26.0.dev0 | |
| - Pytorch 1.13.0+cu117 | |
| - Datasets 2.7.1.dev0 | |
| - Tokenizers 0.13.2 | |