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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_4
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_common_voice-8_4
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: 0.3201
- Wer: 0.3295
## 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: 11
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.9268 | 0.51 | 400 | 1.3204 | 0.9175 |
| 0.7491 | 1.02 | 800 | 0.5880 | 0.6388 |
| 0.4911 | 1.53 | 1200 | 0.4680 | 0.5613 |
| 0.4265 | 2.04 | 1600 | 0.4213 | 0.5059 |
| 0.3473 | 2.55 | 2000 | 0.4199 | 0.4955 |
| 0.3291 | 3.07 | 2400 | 0.4323 | 0.5061 |
| 0.2819 | 3.58 | 2800 | 0.4026 | 0.4490 |
| 0.2628 | 4.09 | 3200 | 0.3831 | 0.4446 |
| 0.2371 | 4.6 | 3600 | 0.3622 | 0.4234 |
| 0.2274 | 5.11 | 4000 | 0.3473 | 0.4012 |
| 0.2051 | 5.62 | 4400 | 0.3471 | 0.3998 |
| 0.1985 | 6.13 | 4800 | 0.3759 | 0.4088 |
| 0.1767 | 6.64 | 5200 | 0.3620 | 0.4012 |
| 0.1707 | 7.15 | 5600 | 0.3415 | 0.3700 |
| 0.1559 | 7.66 | 6000 | 0.3317 | 0.3661 |
| 0.147 | 8.17 | 6400 | 0.3265 | 0.3618 |
| 0.1339 | 8.68 | 6800 | 0.3293 | 0.3586 |
| 0.126 | 9.2 | 7200 | 0.3386 | 0.3458 |
| 0.1149 | 9.71 | 7600 | 0.3305 | 0.3397 |
| 0.1051 | 10.22 | 8000 | 0.3235 | 0.3354 |
| 0.1005 | 10.73 | 8400 | 0.3201 | 0.3295 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 2.1.0
- Tokenizers 0.10.3
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