metadata
language:
- he
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
- he
- generated_from_trainer
model-index:
- name: wav2vec2-xls-r-1b-hebrew
results: []
wav2vec2-xls-r-1b-hebrew
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3533
- Wer: 0.2251
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: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.3587 | 0.47 | 400 | 1.1883 | 0.8392 |
| 1.8377 | 0.95 | 800 | 0.8831 | 0.6852 |
| 1.7118 | 1.42 | 1200 | 0.8031 | 0.6566 |
| 1.6741 | 1.89 | 1600 | 0.7518 | 0.6104 |
| 1.6163 | 2.36 | 2000 | 0.6888 | 0.5591 |
| 1.5782 | 2.84 | 2400 | 0.6580 | 0.5165 |
| 1.5548 | 3.31 | 2800 | 0.6506 | 0.5184 |
| 1.5249 | 3.78 | 3200 | 0.6198 | 0.5028 |
| 1.5078 | 4.26 | 3600 | 0.5992 | 0.4932 |
| 1.4836 | 4.73 | 4000 | 0.5705 | 0.4651 |
| 1.4505 | 5.2 | 4400 | 0.5489 | 0.4508 |
| 1.4481 | 5.67 | 4800 | 0.5577 | 0.4562 |
| 1.4136 | 6.15 | 5200 | 0.5452 | 0.4371 |
| 1.3861 | 6.62 | 5600 | 0.5101 | 0.4087 |
| 1.3772 | 7.09 | 6000 | 0.4933 | 0.3951 |
| 1.3478 | 7.56 | 6400 | 0.4849 | 0.3922 |
| 1.3394 | 8.04 | 6800 | 0.4805 | 0.3892 |
| 1.3095 | 8.51 | 7200 | 0.4839 | 0.3834 |
| 1.306 | 8.98 | 7600 | 0.4611 | 0.3587 |
| 1.2707 | 9.46 | 8000 | 0.4545 | 0.3730 |
| 1.2626 | 9.93 | 8400 | 0.4516 | 0.3524 |
| 1.2412 | 10.4 | 8800 | 0.4314 | 0.3310 |
| 1.2456 | 10.87 | 9200 | 0.4401 | 0.3459 |
| 1.2081 | 11.35 | 9600 | 0.4399 | 0.3356 |
| 1.1998 | 11.82 | 10000 | 0.4195 | 0.3215 |
| 1.1826 | 12.29 | 10400 | 0.4221 | 0.3178 |
| 1.1573 | 12.77 | 10800 | 0.4098 | 0.3084 |
| 1.1416 | 13.24 | 11200 | 0.4086 | 0.3119 |
| 1.1174 | 13.71 | 11600 | 0.3854 | 0.2910 |
| 1.1048 | 14.18 | 12000 | 0.3859 | 0.2824 |
| 1.0748 | 14.66 | 12400 | 0.3854 | 0.2757 |
| 1.0697 | 15.13 | 12800 | 0.3740 | 0.2724 |
| 1.0477 | 15.6 | 13200 | 0.3693 | 0.2643 |
| 1.0356 | 16.08 | 13600 | 0.3727 | 0.2561 |
| 1.0083 | 16.55 | 14000 | 0.3652 | 0.2501 |
| 1.0 | 17.02 | 14400 | 0.3641 | 0.2457 |
| 0.9779 | 17.49 | 14800 | 0.3568 | 0.2409 |
| 0.9596 | 17.97 | 15200 | 0.3558 | 0.2376 |
| 0.946 | 18.44 | 15600 | 0.3591 | 0.2311 |
| 0.9389 | 18.91 | 16000 | 0.3540 | 0.2283 |
| 0.9173 | 19.39 | 16400 | 0.3552 | 0.2265 |
| 0.9122 | 19.86 | 16800 | 0.3535 | 0.2250 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0