--- language: - fa license: apache-2.0 base_model: makhataei/Whisper-Small-Common-Voice tags: - fa-asr - generated_from_trainer datasets: - mozilla-foundation/common_voice_15_0 metrics: - wer model-index: - name: Whisper Small Persian results: [] --- # Whisper Small Persian This model is a fine-tuned version of [makhataei/Whisper-Small-Common-Voice](https://huggingface.co/makhataei/Whisper-Small-Common-Voice) on the Common Voice 15.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.8843 - Wer: 48.6448 ## 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: 14 - eval_batch_size: 10 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 56 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.1801 | 0.39 | 100 | 0.4976 | 49.1260 | | 0.1597 | 0.79 | 200 | 0.4624 | 46.7497 | | 0.0776 | 1.18 | 300 | 0.4794 | 43.1761 | | 0.083 | 1.57 | 400 | 0.4823 | 43.8028 | | 0.0786 | 1.96 | 500 | 0.4883 | 44.3915 | | 0.0331 | 2.36 | 600 | 0.5385 | 46.2437 | | 0.0353 | 2.75 | 700 | 0.5605 | 44.9439 | | 0.0139 | 3.14 | 800 | 0.5941 | 45.2812 | | 0.0152 | 3.53 | 900 | 0.5978 | 49.2930 | | 0.0155 | 3.93 | 1000 | 0.6114 | 49.9777 | | 0.0063 | 4.32 | 1100 | 0.6467 | 50.0041 | | 0.0079 | 4.71 | 1200 | 0.6383 | 48.0875 | | 0.0046 | 5.1 | 1300 | 0.6500 | 45.4995 | | 0.0042 | 5.5 | 1400 | 0.6476 | 47.4492 | | 0.0052 | 5.89 | 1500 | 0.6685 | 52.1870 | | 0.0023 | 6.28 | 1600 | 0.6794 | 44.2510 | | 0.0032 | 6.67 | 1700 | 0.6724 | 45.7161 | | 0.0021 | 7.07 | 1800 | 0.6820 | 47.6013 | | 0.0015 | 7.46 | 1900 | 0.6925 | 46.6720 | | 0.0024 | 7.85 | 2000 | 0.7104 | 50.2902 | | 0.0029 | 8.24 | 2100 | 0.6837 | 46.4173 | | 0.0016 | 8.64 | 2200 | 0.7191 | 46.0088 | | 0.0017 | 9.03 | 2300 | 0.7105 | 47.5964 | | 0.0014 | 9.42 | 2400 | 0.7293 | 44.7603 | | 0.0018 | 9.81 | 2500 | 0.7365 | 49.8966 | | 0.0008 | 10.21 | 2600 | 0.7378 | 47.4740 | | 0.0016 | 10.6 | 2700 | 0.7303 | 45.9691 | | 0.0011 | 10.99 | 2800 | 0.7330 | 47.7254 | | 0.0014 | 11.38 | 2900 | 0.7448 | 44.8579 | | 0.0013 | 11.78 | 3000 | 0.7471 | 46.5116 | | 0.0015 | 12.17 | 3100 | 0.7513 | 47.5699 | | 0.0014 | 12.56 | 3200 | 0.7380 | 46.4008 | | 0.0015 | 12.95 | 3300 | 0.7520 | 45.9658 | | 0.0009 | 13.35 | 3400 | 0.7482 | 49.2269 | | 0.0021 | 13.74 | 3500 | 0.7619 | 47.1234 | | 0.0013 | 14.13 | 3600 | 0.7453 | 49.3956 | | 0.001 | 14.52 | 3700 | 0.7582 | 47.6741 | | 0.0009 | 14.92 | 3800 | 0.7637 | 46.9713 | | 0.0014 | 15.31 | 3900 | 0.7722 | 47.2706 | | 0.001 | 15.7 | 4000 | 0.7692 | 46.9663 | | 0.0003 | 16.09 | 4100 | 0.7744 | 47.1730 | | 0.0004 | 16.49 | 4200 | 0.7842 | 47.3351 | | 0.0003 | 16.88 | 4300 | 0.7784 | 47.0771 | | 0.0002 | 17.27 | 4400 | 0.7879 | 45.7641 | | 0.0005 | 17.66 | 4500 | 0.7965 | 50.0240 | | 0.0004 | 18.06 | 4600 | 0.8001 | 48.4381 | | 0.0002 | 18.45 | 4700 | 0.8016 | 49.0037 | | 0.0002 | 18.84 | 4800 | 0.8066 | 50.0868 | | 0.0009 | 19.23 | 4900 | 0.8021 | 47.2276 | | 0.0005 | 19.63 | 5000 | 0.8162 | 47.3500 | | 0.0003 | 20.02 | 5100 | 0.8091 | 48.7225 | | 0.0003 | 20.41 | 5200 | 0.8060 | 51.5024 | | 0.0003 | 20.8 | 5300 | 0.8220 | 51.4875 | | 0.0003 | 21.2 | 5400 | 0.8098 | 45.8617 | | 0.0003 | 21.59 | 5500 | 0.8132 | 44.8711 | | 0.0009 | 21.98 | 5600 | 0.8006 | 45.3937 | | 0.0003 | 22.37 | 5700 | 0.8008 | 45.6186 | | 0.0002 | 22.77 | 5800 | 0.8081 | 46.3247 | | 0.0002 | 23.16 | 5900 | 0.8082 | 46.1279 | | 0.0002 | 23.55 | 6000 | 0.8238 | 46.1775 | | 0.0005 | 23.95 | 6100 | 0.8119 | 49.9727 | | 0.0002 | 24.34 | 6200 | 0.8315 | 49.0863 | | 0.0001 | 24.73 | 6300 | 0.8224 | 47.2243 | | 0.0001 | 25.12 | 6400 | 0.8259 | 47.1681 | | 0.0001 | 25.52 | 6500 | 0.8219 | 48.5737 | | 0.0002 | 25.91 | 6600 | 0.8400 | 48.9077 | | 0.0005 | 26.3 | 6700 | 0.8319 | 47.5567 | | 0.0001 | 26.69 | 6800 | 0.8394 | 50.2357 | | 0.0001 | 27.09 | 6900 | 0.8480 | 48.4629 | | 0.0001 | 27.48 | 7000 | 0.8498 | 47.1151 | | 0.0002 | 27.87 | 7100 | 0.8342 | 48.9243 | | 0.0003 | 28.26 | 7200 | 0.8184 | 47.3731 | | 0.0001 | 28.66 | 7300 | 0.8278 | 47.9288 | | 0.0002 | 29.05 | 7400 | 0.8439 | 47.8610 | | 0.0001 | 29.44 | 7500 | 0.8461 | 49.9463 | | 0.0001 | 29.83 | 7600 | 0.8449 | 48.4861 | | 0.0001 | 30.23 | 7700 | 0.8512 | 49.0003 | | 0.0001 | 30.62 | 7800 | 0.8555 | 48.2777 | | 0.0001 | 31.01 | 7900 | 0.8543 | 48.6795 | | 0.0001 | 31.4 | 8000 | 0.8566 | 48.7655 | | 0.0001 | 31.8 | 8100 | 0.8605 | 48.6779 | | 0.0 | 32.19 | 8200 | 0.8634 | 49.3691 | | 0.0 | 32.58 | 8300 | 0.8663 | 50.0438 | | 0.0 | 32.97 | 8400 | 0.8685 | 49.7280 | | 0.0 | 33.37 | 8500 | 0.8704 | 49.1641 | | 0.0 | 33.76 | 8600 | 0.8724 | 48.8416 | | 0.0 | 34.15 | 8700 | 0.8736 | 49.2286 | | 0.0 | 34.54 | 8800 | 0.8755 | 48.6134 | | 0.0 | 34.94 | 8900 | 0.8767 | 48.9259 | | 0.0 | 35.33 | 9000 | 0.8778 | 48.9805 | | 0.0 | 35.72 | 9100 | 0.8791 | 49.3212 | | 0.0 | 36.11 | 9200 | 0.8801 | 49.3724 | | 0.0 | 36.51 | 9300 | 0.8813 | 49.4336 | | 0.0 | 36.9 | 9400 | 0.8819 | 49.1045 | | 0.0 | 37.29 | 9500 | 0.8826 | 49.2633 | | 0.0 | 37.68 | 9600 | 0.8832 | 49.4237 | | 0.0 | 38.08 | 9700 | 0.8837 | 48.6316 | | 0.0 | 38.47 | 9800 | 0.8841 | 48.6465 | | 0.0 | 38.86 | 9900 | 0.8842 | 48.9342 | | 0.0 | 39.25 | 10000 | 0.8843 | 48.6448 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.6 - Tokenizers 0.14.1