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# asr_example

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8808
- 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 3.2136        | 50.0  | 500  | 3.1954          | 1.0 |
| 2.8884        | 100.0 | 1000 | 2.9321          | 1.0 |
| 2.7653        | 150.0 | 1500 | 2.8864          | 1.0 |
| 2.7109        | 200.0 | 2000 | 2.8808          | 1.0 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "asr_example", "results": []}]}
transformers safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us