transformers tensorboard safetensors wav2vec2-bert automatic-speech-recognition generated_from_trainer dataset:common_voice_16_0 base_model:ylacombe/w2v-bert-2.0-600m-turkish-colab model-index endpoints_compatible region:us
---
base_model: ylacombe/w2v-bert-2.0-600m-turkish-colab
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: mactest2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_16_0
      type: common_voice_16_0
      config: tr
      split: test
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 0.3088954056695992
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mactest2

This model is a fine-tuned version of [ylacombe/w2v-bert-2.0-600m-turkish-colab](https://huggingface.co/ylacombe/w2v-bert-2.0-600m-turkish-colab) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5663
- Wer: 0.3089

## 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: 5e-05
- 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: 150
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.305         | 1.6   | 100  | 0.4562          | 0.2952 |
| 0.0505        | 3.2   | 200  | 0.4923          | 0.3284 |
| 0.0298        | 4.8   | 300  | 0.4925          | 0.3157 |
| 0.0156        | 6.4   | 400  | 0.5194          | 0.3069 |
| 0.0058        | 8.0   | 500  | 0.5420          | 0.3050 |
| 0.004         | 9.6   | 600  | 0.5663          | 0.3089 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
