transformers tensorboard safetensors wav2vec2-bert generated_from_trainer dataset:common_voice_16_0 base_model:ylacombe/w2v-bert-2.0 model-index endpoints_compatible region:us
---
base_model: ylacombe/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: w2v-bert-2.0-600m-turkish-colab
  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: 0.13727393664832993
---

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# w2v-bert-2.0-600m-turkish-colab

This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1441
- Wer: 0.1373

## 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: 0.0001
- 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: 1000
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.252         | 0.29  | 400  | 0.3121          | 0.3150 |
| 0.2541        | 0.58  | 800  | 0.3786          | 0.3441 |
| 0.2505        | 0.88  | 1200 | 0.4106          | 0.3766 |
| 0.1958        | 1.17  | 1600 | 0.2974          | 0.2877 |
| 0.1686        | 1.46  | 2000 | 0.2854          | 0.2736 |
| 0.1498        | 1.75  | 2400 | 0.2508          | 0.2486 |
| 0.1343        | 2.05  | 2800 | 0.2315          | 0.2263 |
| 0.1045        | 2.34  | 3200 | 0.2207          | 0.2243 |
| 0.0983        | 2.63  | 3600 | 0.2109          | 0.2046 |
| 0.089         | 2.92  | 4000 | 0.1970          | 0.1896 |
| 0.0726        | 3.21  | 4400 | 0.1963          | 0.1799 |
| 0.0552        | 3.51  | 4800 | 0.1879          | 0.1778 |
| 0.0573        | 3.8   | 5200 | 0.1821          | 0.1693 |
| 0.0421        | 4.09  | 5600 | 0.1602          | 0.1517 |
| 0.0363        | 4.38  | 6000 | 0.1564          | 0.1485 |
| 0.0345        | 4.67  | 6400 | 0.1466          | 0.1437 |
| 0.0294        | 4.97  | 6800 | 0.1441          | 0.1373 |


### Framework versions

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