--- license: apache-2.0 base_model: openai/whisper-base tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-base-ckb results: [] --- # whisper-base-ckb This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1420 - Wer: 0.2918 ## 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: 192 - eval_batch_size: 128 - seed: 42 - distributed_type: multi-GPU - num_devices: 6 - total_train_batch_size: 1152 - total_eval_batch_size: 768 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 200 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.3434 | 1.09 | 100 | 0.3840 | 0.6054 | | 0.2089 | 2.17 | 200 | 0.2654 | 0.4740 | | 0.167 | 3.26 | 300 | 0.2246 | 0.4190 | | 0.1452 | 4.35 | 400 | 0.1964 | 0.3803 | | 0.1287 | 5.43 | 500 | 0.1788 | 0.3542 | | 0.1163 | 6.52 | 600 | 0.1650 | 0.3326 | | 0.1068 | 7.61 | 700 | 0.1560 | 0.3155 | | 0.1015 | 8.7 | 800 | 0.1489 | 0.3059 | | 0.0968 | 9.78 | 900 | 0.1440 | 0.2954 | | 0.0939 | 10.87 | 1000 | 0.1420 | 0.2918 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.0.1 - Datasets 2.16.1 - Tokenizers 0.15.0