--- language: - hi license: apache-2.0 base_model: openai/whisper-medium tags: - hf-asr-leaderboard - generated_from_trainer metrics: - wer model-index: - name: Whisper small Hi - CKS 1311 iiitb results: [] --- # Whisper small Hi - CKS 1311 iiitb This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1203 - Wer: 10.8852 - Cer: 3.4179 ## 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: 1.75e-05 - train_batch_size: 16 - 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: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:| | 0.0291 | 8.77 | 500 | 0.1099 | 14.2344 | 4.1970 | | 0.004 | 17.54 | 1000 | 0.1114 | 10.8852 | 3.4682 | | 0.0001 | 26.32 | 1500 | 0.1185 | 10.7656 | 3.3677 | | 0.0 | 35.09 | 2000 | 0.1203 | 10.8852 | 3.4179 | ### Framework versions - Transformers 4.36.0.dev0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1