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# w2v-bert-2.0-turkish-colab-CV6.1

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_6_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1978
- Wer: 0.1838

## 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: 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.4016        | 0.92  | 100  | 2.4338          | 1.0428 |
| 0.5644        | 1.83  | 200  | 0.2224          | 0.1936 |
| 0.1692        | 2.75  | 300  | 0.1978          | 0.1838 |


### Framework versions

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

{"tags": ["generated_from_trainer"], "datasets": ["common_voice_6_1"], "metrics": ["wer"], "base_model": "ylacombe/w2v-bert-2.0", "model-index": [{"name": "w2v-bert-2.0-turkish-colab-CV6.1", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "common_voice_6_1", "type": "common_voice_6_1", "config": "tr", "split": "test", "args": "tr"}, "metrics": [{"type": "wer", "value": 0.18384230415687877, "name": "Wer"}]}]}]}
transformers tensorboard safetensors wav2vec2-bert generated_from_trainer dataset:common_voice_6_1 base_model:ylacombe/w2v-bert-2.0 model-index endpoints_compatible region:us