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---
language:
- tr
base_model: ylacombe/w2v-bert-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_16_0
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-tr-demo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: MOZILLA-FOUNDATION/COMMON_VOICE_16_0 - TR
type: common_voice_16_0
config: tr
split: test
args: 'Config: tr, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 1.0
---
<!-- 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 [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the MOZILLA-FOUNDATION/COMMON_VOICE_16_0 - TR dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
## 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: 0.007448827845832091
- train_batch_size: 20
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| No log | 0.27 | 300 | 3.2930 | 1.0 |
| 5.6462 | 0.55 | 600 | 3.4159 | 1.0 |
| 5.6462 | 0.82 | 900 | 3.4422 | 1.0 |
| 3.3522 | 1.1 | 1200 | 3.3719 | 1.0 |
| 3.2605 | 1.37 | 1500 | 3.4026 | 1.0 |
| 3.2605 | 1.64 | 1800 | 3.4448 | 1.0 |
| 3.2766 | 1.92 | 2100 | 3.4736 | 0.9999 |
| 3.2766 | 2.19 | 2400 | 3.9828 | 1.0 |
| 3.2853 | 2.47 | 2700 | 3.5532 | 1.0 |
| 3.3389 | 2.74 | 3000 | 3.7819 | 1.0 |
| 3.3389 | 3.01 | 3300 | 3.2250 | 1.0 |
| 3.2186 | 3.29 | 3600 | 3.2373 | 1.0 |
| 3.2186 | 3.56 | 3900 | 3.2162 | 1.0 |
| 3.1916 | 3.84 | 4200 | 3.2368 | 1.0 |
| 3.2188 | 4.11 | 4500 | 3.2377 | 1.0 |
| 3.2188 | 4.38 | 4800 | 3.4207 | 1.0 |
| 5.3067 | 4.66 | 5100 | nan | 1.0 |
| 5.3067 | 4.93 | 5400 | nan | 1.0 |
| 0.0 | 5.21 | 5700 | nan | 1.0 |
| 0.0 | 5.48 | 6000 | nan | 1.0 |
| 0.0 | 5.75 | 6300 | nan | 1.0 |
| 0.0 | 6.03 | 6600 | nan | 1.0 |
| 0.0 | 6.3 | 6900 | nan | 1.0 |
| 0.0 | 6.58 | 7200 | nan | 1.0 |
| 0.0 | 6.85 | 7500 | nan | 1.0 |
| 0.0 | 7.12 | 7800 | nan | 1.0 |
| 0.0 | 7.4 | 8100 | nan | 1.0 |
| 0.0 | 7.67 | 8400 | nan | 1.0 |
| 0.0 | 7.95 | 8700 | nan | 1.0 |
| 0.0 | 8.22 | 9000 | nan | 1.0 |
| 0.0 | 8.49 | 9300 | nan | 1.0 |
| 0.0 | 8.77 | 9600 | nan | 1.0 |
| 0.0 | 9.04 | 9900 | nan | 1.0 |
| 0.0 | 9.32 | 10200 | nan | 1.0 |
| 0.0 | 9.59 | 10500 | nan | 1.0 |
| 0.0 | 9.86 | 10800 | nan | 1.0 |
| 0.0 | 10.14 | 11100 | nan | 1.0 |
| 0.0 | 10.41 | 11400 | nan | 1.0 |
| 0.0 | 10.68 | 11700 | nan | 1.0 |
| 0.0 | 10.96 | 12000 | nan | 1.0 |
| 0.0 | 11.23 | 12300 | nan | 1.0 |
| 0.0 | 11.51 | 12600 | nan | 1.0 |
| 0.0 | 11.78 | 12900 | nan | 1.0 |
| 0.0 | 12.05 | 13200 | nan | 1.0 |
| 0.0 | 12.33 | 13500 | nan | 1.0 |
| 0.0 | 12.6 | 13800 | nan | 1.0 |
| 0.0 | 12.88 | 14100 | nan | 1.0 |
| 0.0 | 13.15 | 14400 | nan | 1.0 |
| 0.0 | 13.42 | 14700 | nan | 1.0 |
| 0.0 | 13.7 | 15000 | nan | 1.0 |
| 0.0 | 13.97 | 15300 | nan | 1.0 |
| 0.0 | 14.25 | 15600 | nan | 1.0 |
| 0.0 | 14.52 | 15900 | nan | 1.0 |
| 0.0 | 14.79 | 16200 | nan | 1.0 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.15.0
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