---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
model-index:
- name: xls_r_300m_cv6_1-turkish-istech
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_6_1
      type: common_voice_6_1
      config: tr
      split: test
      args: tr
    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. -->

# xls_r_300m_cv6_1-turkish-istech

This model is a fine-tuned version of [](https://huggingface.co/) on the common_voice_6_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1644
- 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 0.5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| 8.538         | 0.0920 | 20   | 3.4802          | 1.0 |
| 3.2474        | 0.1839 | 40   | 3.2474          | 1.0 |
| 3.1785        | 0.2759 | 60   | 3.2152          | 1.0 |
| 3.145         | 0.3678 | 80   | 3.1730          | 1.0 |
| 3.1493        | 0.4598 | 100  | 3.1644          | 1.0 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1