|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- common_voice |
|
|
model-index: |
|
|
- name: wav2vec2-large-xls-r-300m-turkish-colab |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# wav2vec2-large-xls-r-300m-turkish-colab |
|
|
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.7126 |
|
|
- Wer: 0.8198 |
|
|
|
|
|
## 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: 1 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 4 |
|
|
- total_train_batch_size: 4 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 120 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:------:|:-----:|:---------------:|:------:| |
|
|
| 6.7419 | 2.38 | 200 | 3.1913 | 1.0 | |
|
|
| 3.0446 | 4.76 | 400 | 2.3247 | 1.0 | |
|
|
| 1.3163 | 7.14 | 600 | 1.2629 | 0.9656 | |
|
|
| 0.6058 | 9.52 | 800 | 1.2203 | 0.9343 | |
|
|
| 0.3687 | 11.9 | 1000 | 1.2157 | 0.8849 | |
|
|
| 0.2644 | 14.29 | 1200 | 1.3693 | 0.8992 | |
|
|
| 0.2147 | 16.67 | 1400 | 1.3321 | 0.8623 | |
|
|
| 0.1962 | 19.05 | 1600 | 1.3476 | 0.8886 | |
|
|
| 0.1631 | 21.43 | 1800 | 1.3984 | 0.8755 | |
|
|
| 0.15 | 23.81 | 2000 | 1.4602 | 0.8798 | |
|
|
| 0.1311 | 26.19 | 2200 | 1.4727 | 0.8836 | |
|
|
| 0.1174 | 28.57 | 2400 | 1.5257 | 0.8805 | |
|
|
| 0.1155 | 30.95 | 2600 | 1.4697 | 0.9337 | |
|
|
| 0.1046 | 33.33 | 2800 | 1.6076 | 0.8667 | |
|
|
| 0.1063 | 35.71 | 3000 | 1.5012 | 0.8861 | |
|
|
| 0.0996 | 38.1 | 3200 | 1.6204 | 0.8605 | |
|
|
| 0.088 | 40.48 | 3400 | 1.4788 | 0.8586 | |
|
|
| 0.089 | 42.86 | 3600 | 1.5983 | 0.8648 | |
|
|
| 0.0805 | 45.24 | 3800 | 1.5045 | 0.8298 | |
|
|
| 0.0718 | 47.62 | 4000 | 1.6361 | 0.8611 | |
|
|
| 0.0718 | 50.0 | 4200 | 1.5088 | 0.8548 | |
|
|
| 0.0649 | 52.38 | 4400 | 1.5491 | 0.8554 | |
|
|
| 0.0685 | 54.76 | 4600 | 1.5939 | 0.8442 | |
|
|
| 0.0588 | 57.14 | 4800 | 1.6321 | 0.8536 | |
|
|
| 0.0591 | 59.52 | 5000 | 1.6468 | 0.8442 | |
|
|
| 0.0529 | 61.9 | 5200 | 1.6086 | 0.8661 | |
|
|
| 0.0482 | 64.29 | 5400 | 1.6622 | 0.8517 | |
|
|
| 0.0396 | 66.67 | 5600 | 1.6191 | 0.8436 | |
|
|
| 0.0463 | 69.05 | 5800 | 1.6231 | 0.8661 | |
|
|
| 0.0415 | 71.43 | 6000 | 1.6874 | 0.8511 | |
|
|
| 0.0383 | 73.81 | 6200 | 1.7054 | 0.8411 | |
|
|
| 0.0411 | 76.19 | 6400 | 1.7073 | 0.8486 | |
|
|
| 0.0346 | 78.57 | 6600 | 1.7137 | 0.8342 | |
|
|
| 0.0318 | 80.95 | 6800 | 1.6523 | 0.8329 | |
|
|
| 0.0299 | 83.33 | 7000 | 1.6893 | 0.8579 | |
|
|
| 0.029 | 85.71 | 7200 | 1.7162 | 0.8429 | |
|
|
| 0.025 | 88.1 | 7400 | 1.7589 | 0.8529 | |
|
|
| 0.025 | 90.48 | 7600 | 1.7581 | 0.8398 | |
|
|
| 0.0232 | 92.86 | 7800 | 1.8459 | 0.8442 | |
|
|
| 0.0215 | 95.24 | 8000 | 1.7942 | 0.8448 | |
|
|
| 0.0222 | 97.62 | 8200 | 1.6848 | 0.8442 | |
|
|
| 0.0179 | 100.0 | 8400 | 1.7223 | 0.8298 | |
|
|
| 0.0176 | 102.38 | 8600 | 1.7426 | 0.8404 | |
|
|
| 0.016 | 104.76 | 8800 | 1.7501 | 0.8411 | |
|
|
| 0.0153 | 107.14 | 9000 | 1.7185 | 0.8235 | |
|
|
| 0.0136 | 109.52 | 9200 | 1.7250 | 0.8292 | |
|
|
| 0.0117 | 111.9 | 9400 | 1.7159 | 0.8185 | |
|
|
| 0.0123 | 114.29 | 9600 | 1.7135 | 0.8248 | |
|
|
| 0.0121 | 116.67 | 9800 | 1.7189 | 0.8210 | |
|
|
| 0.0116 | 119.05 | 10000 | 1.7126 | 0.8198 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.11.3 |
|
|
- Pytorch 1.10.0+cu113 |
|
|
- Datasets 1.18.3 |
|
|
- Tokenizers 0.10.3 |
|
|
|
