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# w2v-bert-2.0-czech-colab-cv16

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1023
- Wer: 0.0573

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.5297        | 0.66  | 300  | 0.1448          | 0.1299 |
| 0.0886        | 1.32  | 600  | 0.1353          | 0.1051 |
| 0.0717        | 1.98  | 900  | 0.1157          | 0.0861 |
| 0.0463        | 2.64  | 1200 | 0.0994          | 0.0759 |
| 0.0404        | 3.3   | 1500 | 0.1054          | 0.0724 |
| 0.0314        | 3.96  | 1800 | 0.0915          | 0.0694 |
| 0.0227        | 4.63  | 2100 | 0.0926          | 0.0664 |
| 0.0205        | 5.29  | 2400 | 0.0992          | 0.0652 |
| 0.0161        | 5.95  | 2700 | 0.0932          | 0.0654 |
| 0.0124        | 6.61  | 3000 | 0.0902          | 0.0629 |
| 0.0097        | 7.27  | 3300 | 0.0970          | 0.0612 |
| 0.0081        | 7.93  | 3600 | 0.0946          | 0.0602 |
| 0.0054        | 8.59  | 3900 | 0.0962          | 0.0588 |
| 0.0048        | 9.25  | 4200 | 0.1029          | 0.0579 |
| 0.0034        | 9.91  | 4500 | 0.1023          | 0.0573 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["common_voice_16_0"], "metrics": ["wer"], "base_model": "facebook/w2v-bert-2.0", "model-index": [{"name": "w2v-bert-2.0-czech-colab-cv16", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "common_voice_16_0", "type": "common_voice_16_0", "config": "cs", "split": "test", "args": "cs"}, "metrics": [{"type": "wer", "value": 0.05733702722973076, "name": "Wer"}]}]}]}
transformers tensorboard safetensors wav2vec2-bert automatic-speech-recognition generated_from_trainer dataset:common_voice_16_0 base_model:facebook/w2v-bert-2.0 license:mit model-index endpoints_compatible has_space region:us