|
--- |
|
language: |
|
- sv-SE |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- common_voice |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: wav2vec2-common_voice-tr-demo |
|
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-common_voice-tr-demo |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - SV-SE dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5528 |
|
- Wer: 0.3811 |
|
|
|
## 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: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 15.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| No log | 0.74 | 100 | 3.4444 | 1.0 | |
|
| No log | 1.47 | 200 | 2.9421 | 1.0 | |
|
| No log | 2.21 | 300 | 2.2802 | 1.0137 | |
|
| No log | 2.94 | 400 | 0.9683 | 0.7611 | |
|
| 3.7264 | 3.68 | 500 | 0.7941 | 0.6594 | |
|
| 3.7264 | 4.41 | 600 | 0.6695 | 0.5751 | |
|
| 3.7264 | 5.15 | 700 | 0.6507 | 0.5314 | |
|
| 3.7264 | 5.88 | 800 | 0.5731 | 0.4927 | |
|
| 3.7264 | 6.62 | 900 | 0.5723 | 0.4580 | |
|
| 0.4592 | 7.35 | 1000 | 0.5913 | 0.4479 | |
|
| 0.4592 | 8.09 | 1100 | 0.5562 | 0.4423 | |
|
| 0.4592 | 8.82 | 1200 | 0.5566 | 0.4292 | |
|
| 0.4592 | 9.56 | 1300 | 0.5492 | 0.4303 | |
|
| 0.4592 | 10.29 | 1400 | 0.5665 | 0.4331 | |
|
| 0.2121 | 11.03 | 1500 | 0.5610 | 0.4084 | |
|
| 0.2121 | 11.76 | 1600 | 0.5703 | 0.4014 | |
|
| 0.2121 | 12.5 | 1700 | 0.5669 | 0.3898 | |
|
| 0.2121 | 13.24 | 1800 | 0.5586 | 0.3962 | |
|
| 0.2121 | 13.97 | 1900 | 0.5656 | 0.3897 | |
|
| 0.1326 | 14.71 | 2000 | 0.5565 | 0.3813 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.0.dev0 |
|
- Pytorch 1.10.1+cu113 |
|
- Datasets 1.18.0 |
|
- Tokenizers 0.10.3 |
|
|
