Whisper Tanglish Voice Generalized 5000

--- library_name: transformers base_model: Badri0510/whisper-tanglish-5e5-8000-experiment tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-tanglish-voice-generalized-5000 results: [] --- # whisper-tanglish-voice-generalized-5000 This model is a fine-tuned version of [Badri0510/whisper-tanglish-5e5-8000-experiment](https://huggingface.co/Badri0510/whisper-tanglish-5e5-8000-experiment) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0006 - Wer: 0.2142 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 200 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:-----:|:---------------:|:------:| | 0.0782 | 0.05 | 500 | 0.0422 | 0.2990 | | 0.1172 | 0.1 | 1000 | 0.0463 | 0.2849 | | 0.0989 | 1.0372 | 1500 | 0.0302 | 0.2789 | | 0.1372 | 1.0872 | 2000 | 0.0286 | 0.2632 | | 0.0617 | 2.0244 | 2500 | 0.0181 | 0.2471 | | 0.0990 | 2.0744 | 3000 | 0.0197 | 0.2850 | | 0.0499 | 3.0124 | 3500 | 0.0230 | 0.2724 | | 0.0536 | 3.0624 | 4000 | 0.0160 | 0.2547 | | 0.0455 | 4.0013 | 4500 | 0.0099 | 0.2417 | | 0.0264 | 4.0513 | 5000 | 0.0087 | 0.2301 | | 0.0317 | 4.1013 | 5500 | 0.0050 | 0.2236 | | 0.0127 | 5.0388 | 6000 | 0.0045 | 0.2206 | | 0.0155 | 5.0888 | 6500 | 0.0037 | 0.2223 | | 0.0070 | 6.0272 | 7000 | 0.0022 | 0.2174 | | 0.0058 | 6.0772 | 7500 | 0.0018 | 0.2164 | | 0.0023 | 7.0135 | 8000 | 0.0013 | 0.2148 | | 0.0029 | 7.0635 | 8500 | 0.0006 | 0.2141 | | 0.0027 | 8.0025 | 9000 | 0.0006 | 0.2141 | | 0.0024 | 8.0525 | 9500 | 0.0006 | 0.2142 | | 0.0098 | 8.1025 | 10000 | 0.0006 | 0.2142 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2