---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- google/fleurs
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-en-finetune
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: GOOGLE/FLEURS - EN_US
      type: fleurs
      config: en_us
      split: test
      args: 'Config: en_us, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.25982311149775267
---

<!-- 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-common_voice-en-finetune

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the GOOGLE/FLEURS - EN_US dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3436
- Wer: 0.2598

## 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: 0.0003
- 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: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 1.0870 | 100  | 3.5106          | 1.0    |
| No log        | 2.1739 | 200  | 2.9226          | 1.0    |
| No log        | 3.2609 | 300  | 2.8745          | 1.0    |
| No log        | 4.3478 | 400  | 1.8100          | 0.9804 |
| 3.7609        | 5.4348 | 500  | 0.4771          | 0.4207 |
| 3.7609        | 6.5217 | 600  | 0.3808          | 0.3484 |
| 3.7609        | 7.6087 | 700  | 0.3408          | 0.2872 |
| 3.7609        | 8.6957 | 800  | 0.3479          | 0.2719 |
| 3.7609        | 9.7826 | 900  | 0.3437          | 0.2604 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1