hubert-large-hre-v1
This model is a fine-tuned version of facebook/hubert-large-ls960-ft on the hre-audio-dataset8 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7225
- Cer Ortho: 53.9483
- Cer: 46.5317
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer Ortho | Cer |
|---|---|---|---|---|---|
| 3.3539 | 0.4608 | 100 | 3.2333 | 99.0488 | 99.0248 |
| 2.1675 | 0.9217 | 200 | 2.0411 | 84.2247 | 82.1343 |
| 1.2398 | 1.3825 | 300 | 1.2868 | 69.8313 | 66.8261 |
| 1.0372 | 1.8433 | 400 | 1.0814 | 62.0603 | 60.5520 |
| 0.9143 | 2.3041 | 500 | 0.9490 | 64.1780 | 59.4296 |
| 0.8814 | 2.7650 | 600 | 0.8401 | 61.5757 | 56.4857 |
| 0.7726 | 3.2258 | 700 | 0.8606 | 58.6504 | 55.9522 |
| 0.8116 | 3.6866 | 800 | 0.7670 | 67.9648 | 54.9402 |
| 0.6826 | 4.1475 | 900 | 0.7524 | 67.7315 | 54.1490 |
| 0.5953 | 4.6083 | 1000 | 0.7812 | 66.7085 | 53.5051 |
| 0.6733 | 5.0691 | 1100 | 0.8268 | 63.0294 | 54.0202 |
| 0.6596 | 5.5300 | 1200 | 0.7109 | 62.9935 | 52.6403 |
| 0.5065 | 5.9908 | 1300 | 0.7529 | 65.4702 | 51.6651 |
| 0.4880 | 6.4516 | 1400 | 0.7643 | 65.0395 | 51.5731 |
| 0.5539 | 6.9124 | 1500 | 0.7285 | 65.6676 | 51.8123 |
| 0.5446 | 7.3733 | 1600 | 0.7215 | 62.7782 | 51.1316 |
| 0.4763 | 7.8341 | 1700 | 0.7669 | 64.2498 | 51.2971 |
| 0.4665 | 8.2949 | 1800 | 0.6920 | 63.8729 | 50.1564 |
| 0.4189 | 8.7558 | 1900 | 0.6964 | 64.4472 | 49.9172 |
| 0.4124 | 9.2166 | 2000 | 0.7164 | 58.8119 | 49.9540 |
| 0.3157 | 9.6774 | 2100 | 0.6939 | 56.5506 | 49.9356 |
| 0.3570 | 10.1382 | 2200 | 0.7459 | 54.9174 | 49.4756 |
| 0.3523 | 10.5991 | 2300 | 0.6848 | 50.9512 | 48.7029 |
| 0.3624 | 11.0599 | 2400 | 0.6860 | 50.6281 | 48.6293 |
| 0.3054 | 11.5207 | 2500 | 0.7821 | 51.3640 | 48.8684 |
| 0.3190 | 11.9816 | 2600 | 0.8238 | 52.4587 | 49.2732 |
| 0.3675 | 12.4424 | 2700 | 0.7947 | 57.9864 | 49.3284 |
| 0.4182 | 12.9032 | 2800 | 0.7326 | 57.7889 | 48.3533 |
| 0.2994 | 13.3641 | 2900 | 0.7606 | 55.7251 | 48.4085 |
| 0.2666 | 13.8249 | 3000 | 0.7204 | 56.0660 | 47.6909 |
| 0.2769 | 14.2857 | 3100 | 0.7308 | 54.8636 | 47.3229 |
| 0.2843 | 14.7465 | 3200 | 0.7531 | 56.6403 | 47.8381 |
| 0.2587 | 15.2074 | 3300 | 0.7166 | 56.1378 | 47.3965 |
| 0.2386 | 15.6682 | 3400 | 0.6969 | 52.9433 | 47.2125 |
| 0.2284 | 16.1290 | 3500 | 0.7046 | 51.2563 | 46.8813 |
| 0.1806 | 16.5899 | 3600 | 0.7277 | 52.7997 | 47.1205 |
| 0.2266 | 17.0507 | 3700 | 0.6840 | 53.8227 | 46.5133 |
| 0.1728 | 17.5115 | 3800 | 0.7269 | 53.8586 | 46.5317 |
| 0.1993 | 17.9724 | 3900 | 0.7186 | 54.5585 | 46.5869 |
| 0.1944 | 18.4332 | 4000 | 0.7228 | 54.5226 | 46.3109 |
| 0.1923 | 18.8940 | 4100 | 0.7402 | 54.7739 | 46.8077 |
| 0.2191 | 19.3548 | 4200 | 0.7298 | 53.9842 | 46.5501 |
| 0.1717 | 19.8157 | 4300 | 0.7230 | 54.0022 | 46.5133 |
| 0.1761 | 20.0 | 4340 | 0.7225 | 53.9483 | 46.5317 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 2.18.0
- Tokenizers 0.22.2