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---
language:
- tr
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: hello_2b
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. -->
# hello_2b
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-2b](https://huggingface.co/facebook/wav2vec2-xls-r-2b) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2725
- Wer: 0.9531
## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.1646 | 0.92 | 100 | 3.2106 | 1.0 |
| 0.368 | 1.85 | 200 | 2.9963 | 1.0 |
| 0.2252 | 2.77 | 300 | 2.8078 | 0.9999 |
| 0.1546 | 3.7 | 400 | 2.3458 | 0.9996 |
| 0.1468 | 4.63 | 500 | 2.0086 | 0.9986 |
| 0.1261 | 5.55 | 600 | 1.8269 | 0.9985 |
| 0.1206 | 6.48 | 700 | 1.7347 | 0.9956 |
| 0.1959 | 7.4 | 800 | 1.6819 | 0.9955 |
| 0.0502 | 8.33 | 900 | 1.6809 | 0.9965 |
| 0.0811 | 9.26 | 1000 | 1.6674 | 0.9916 |
| 0.0534 | 10.18 | 1100 | 1.5719 | 0.9898 |
| 0.0402 | 11.11 | 1200 | 1.4620 | 0.9821 |
| 0.057 | 12.04 | 1300 | 1.3015 | 0.9554 |
| 0.0385 | 12.96 | 1400 | 1.3798 | 0.9600 |
| 0.0422 | 13.88 | 1500 | 1.3538 | 0.9699 |
| 0.014 | 14.81 | 1600 | 1.2507 | 0.9443 |
| 0.0232 | 15.74 | 1700 | 1.3318 | 0.9465 |
| 0.0554 | 16.66 | 1800 | 1.2784 | 0.9462 |
| 0.0316 | 17.59 | 1900 | 1.2503 | 0.9481 |
| 0.0524 | 18.51 | 2000 | 1.3920 | 0.9604 |
| 0.0142 | 19.44 | 2100 | 1.4224 | 0.9698 |
| 0.0288 | 20.37 | 2200 | 1.3475 | 0.9635 |
| 0.0106 | 21.29 | 2300 | 1.2232 | 0.9264 |
| 0.0396 | 22.22 | 2400 | 1.3323 | 0.9615 |
| 0.0349 | 23.15 | 2500 | 1.2741 | 0.9587 |
| 0.0121 | 24.07 | 2600 | 1.2671 | 0.9586 |
| 0.0224 | 24.99 | 2700 | 1.3001 | 0.9611 |
| 0.0449 | 25.92 | 2800 | 1.2777 | 0.9572 |
| 0.0186 | 26.85 | 2900 | 1.2766 | 0.9607 |
| 0.0365 | 27.77 | 3000 | 1.2935 | 0.9598 |
| 0.0105 | 28.7 | 3100 | 1.2761 | 0.9588 |
| 0.021 | 29.63 | 3200 | 1.2686 | 0.9528 |
### Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0
- Datasets 1.15.2.dev0
- Tokenizers 0.10.3
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