kiranpantha/whisper-large-v3-nepali
This model is a fine-tuned version of kiranpantha/whisper-large-v3-nepali on the OpenSLR54 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4213
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 14 | 0.3574 |
| 0.6204 | 2.0 | 28 | 0.3134 |
| 0.6204 | 3.0 | 42 | 0.3488 |
| 0.1212 | 4.0 | 56 | 0.3598 |
| 0.1212 | 5.0 | 70 | 0.4100 |
| 0.0805 | 6.0 | 84 | 0.3659 |
| 0.0805 | 7.0 | 98 | 0.3481 |
| 0.063 | 8.0 | 112 | 0.3967 |
| 0.0304 | 9.0 | 126 | 0.3466 |
| 0.0304 | 10.0 | 140 | 0.3495 |
| 0.0287 | 11.0 | 154 | 0.3672 |
| 0.0287 | 12.0 | 168 | 0.3762 |
| 0.0173 | 13.0 | 182 | 0.3518 |
| 0.0173 | 14.0 | 196 | 0.3574 |
| 0.0205 | 15.0 | 210 | 0.3874 |
| 0.0205 | 16.0 | 224 | 0.3449 |
| 0.0127 | 17.0 | 238 | 0.3697 |
| 0.0138 | 18.0 | 252 | 0.3428 |
| 0.0138 | 19.0 | 266 | 0.3290 |
| 0.0096 | 20.0 | 280 | 0.3459 |
| 0.0096 | 21.0 | 294 | 0.3702 |
| 0.0105 | 22.0 | 308 | 0.3467 |
| 0.0105 | 23.0 | 322 | 0.3903 |
| 0.0046 | 24.0 | 336 | 0.3670 |
| 0.0019 | 25.0 | 350 | 0.3859 |
| 0.0019 | 26.0 | 364 | 0.3900 |
| 0.0006 | 27.0 | 378 | 0.3857 |
| 0.0006 | 28.0 | 392 | 0.3836 |
| 0.0004 | 29.0 | 406 | 0.3851 |
| 0.0004 | 30.0 | 420 | 0.3864 |
| 0.0003 | 31.0 | 434 | 0.3878 |
| 0.0003 | 32.0 | 448 | 0.3899 |
| 0.0003 | 33.0 | 462 | 0.3904 |
| 0.0003 | 34.0 | 476 | 0.3917 |
| 0.0003 | 35.0 | 490 | 0.3925 |
| 0.0002 | 36.0 | 504 | 0.3939 |
| 0.0002 | 37.0 | 518 | 0.3946 |
| 0.0002 | 38.0 | 532 | 0.3957 |
| 0.0002 | 39.0 | 546 | 0.3958 |
| 0.0002 | 40.0 | 560 | 0.3966 |
| 0.0002 | 41.0 | 574 | 0.3977 |
| 0.0002 | 42.0 | 588 | 0.3984 |
| 0.0002 | 43.0 | 602 | 0.3990 |
| 0.0002 | 44.0 | 616 | 0.3998 |
| 0.0002 | 45.0 | 630 | 0.4008 |
| 0.0002 | 46.0 | 644 | 0.4013 |
| 0.0002 | 47.0 | 658 | 0.4016 |
| 0.0002 | 48.0 | 672 | 0.4023 |
| 0.0002 | 49.0 | 686 | 0.4028 |
| 0.0002 | 50.0 | 700 | 0.4034 |
| 0.0002 | 51.0 | 714 | 0.4041 |
| 0.0001 | 52.0 | 728 | 0.4048 |
| 0.0001 | 53.0 | 742 | 0.4054 |
| 0.0001 | 54.0 | 756 | 0.4060 |
| 0.0001 | 55.0 | 770 | 0.4064 |
| 0.0001 | 56.0 | 784 | 0.4072 |
| 0.0001 | 57.0 | 798 | 0.4077 |
| 0.0001 | 58.0 | 812 | 0.4081 |
| 0.0001 | 59.0 | 826 | 0.4088 |
| 0.0001 | 60.0 | 840 | 0.4097 |
| 0.0001 | 61.0 | 854 | 0.4104 |
| 0.0001 | 62.0 | 868 | 0.4107 |
| 0.0001 | 63.0 | 882 | 0.4114 |
| 0.0001 | 64.0 | 896 | 0.4122 |
| 0.0001 | 65.0 | 910 | 0.4122 |
| 0.0001 | 66.0 | 924 | 0.4128 |
| 0.0001 | 67.0 | 938 | 0.4136 |
| 0.0001 | 68.0 | 952 | 0.4138 |
| 0.0001 | 69.0 | 966 | 0.4141 |
| 0.0001 | 70.0 | 980 | 0.4144 |
| 0.0001 | 71.0 | 994 | 0.4150 |
| 0.0001 | 72.0 | 1008 | 0.4155 |
| 0.0001 | 73.0 | 1022 | 0.4156 |
| 0.0001 | 74.0 | 1036 | 0.4161 |
| 0.0001 | 75.0 | 1050 | 0.4163 |
| 0.0001 | 76.0 | 1064 | 0.4167 |
| 0.0001 | 77.0 | 1078 | 0.4171 |
| 0.0001 | 78.0 | 1092 | 0.4174 |
| 0.0001 | 79.0 | 1106 | 0.4176 |
| 0.0001 | 80.0 | 1120 | 0.4177 |
| 0.0001 | 81.0 | 1134 | 0.4179 |
| 0.0001 | 82.0 | 1148 | 0.4183 |
| 0.0001 | 83.0 | 1162 | 0.4186 |
| 0.0001 | 84.0 | 1176 | 0.4187 |
| 0.0001 | 85.0 | 1190 | 0.4192 |
| 0.0001 | 86.0 | 1204 | 0.4194 |
| 0.0001 | 87.0 | 1218 | 0.4197 |
| 0.0001 | 88.0 | 1232 | 0.4198 |
| 0.0001 | 89.0 | 1246 | 0.4201 |
| 0.0001 | 90.0 | 1260 | 0.4204 |
| 0.0001 | 91.0 | 1274 | 0.4205 |
| 0.0001 | 92.0 | 1288 | 0.4206 |
| 0.0001 | 93.0 | 1302 | 0.4208 |
| 0.0001 | 94.0 | 1316 | 0.4208 |
| 0.0001 | 95.0 | 1330 | 0.4209 |
| 0.0001 | 96.0 | 1344 | 0.4211 |
| 0.0001 | 97.0 | 1358 | 0.4211 |
| 0.0001 | 98.0 | 1372 | 0.4211 |
| 0.0001 | 99.0 | 1386 | 0.4212 |
| 0.0001 | 100.0 | 1400 | 0.4213 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.21.0