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---
license: apache-2.0
language: tt
tags:
- generated_from_trainer
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xlsr-53-W2V2-TATAR-SMALL
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice tt
type: common_voice
args: tt
metrics:
- name: Test WER
type: wer
value: 53.16
---
<!-- 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-xlsr-53-W2V2-TATAR-SMALL
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4714
- Wer: 0.5316
## 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: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.2446 | 1.17 | 400 | 3.2621 | 1.0 |
| 1.739 | 2.35 | 800 | 0.5832 | 0.7688 |
| 0.4718 | 3.52 | 1200 | 0.4785 | 0.6824 |
| 0.3574 | 4.69 | 1600 | 0.4814 | 0.6792 |
| 0.2946 | 5.86 | 2000 | 0.4484 | 0.6506 |
| 0.2674 | 7.04 | 2400 | 0.4612 | 0.6225 |
| 0.2349 | 8.21 | 2800 | 0.4600 | 0.6050 |
| 0.2206 | 9.38 | 3200 | 0.4772 | 0.6048 |
| 0.2072 | 10.56 | 3600 | 0.4676 | 0.6106 |
| 0.1984 | 11.73 | 4000 | 0.4816 | 0.6079 |
| 0.1793 | 12.9 | 4400 | 0.4616 | 0.5836 |
| 0.172 | 14.08 | 4800 | 0.4808 | 0.5860 |
| 0.1624 | 15.25 | 5200 | 0.4854 | 0.5820 |
| 0.156 | 16.42 | 5600 | 0.4609 | 0.5656 |
| 0.1448 | 17.59 | 6000 | 0.4926 | 0.5817 |
| 0.1406 | 18.77 | 6400 | 0.4638 | 0.5654 |
| 0.1337 | 19.94 | 6800 | 0.4731 | 0.5652 |
| 0.1317 | 21.11 | 7200 | 0.4861 | 0.5639 |
| 0.1179 | 22.29 | 7600 | 0.4766 | 0.5521 |
| 0.1197 | 23.46 | 8000 | 0.4824 | 0.5584 |
| 0.1096 | 24.63 | 8400 | 0.5006 | 0.5559 |
| 0.1038 | 25.81 | 8800 | 0.4994 | 0.5440 |
| 0.0992 | 26.98 | 9200 | 0.4867 | 0.5405 |
| 0.0984 | 28.15 | 9600 | 0.4798 | 0.5361 |
| 0.0943 | 29.33 | 10000 | 0.4714 | 0.5316 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
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