---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- librispeech_asr_dummy
metrics:
- wer
model-index:
- name: wav2vec2-base-librispeech
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: librispeech_asr_dummy
      type: librispeech_asr_dummy
      config: clean
      split: None
      args: clean
    metrics:
    - name: Wer
      type: wer
      value: 0.4069767441860465
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-base-librispeech

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the librispeech_asr_dummy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9548
- Wer: 0.4070

## 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: 4
- 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: 1000
- num_epochs: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.4865        | 29.41  | 500  | 3.5010          | 1.0    |
| 1.112         | 58.82  | 1000 | 1.0382          | 0.4767 |
| 0.111         | 88.24  | 1500 | 0.9833          | 0.5116 |
| 0.0438        | 117.65 | 2000 | 0.9302          | 0.4302 |
| 0.0241        | 147.06 | 2500 | 0.9548          | 0.4070 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2