---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: wav2vec2-large-xlsr-53-english-pronunciation-evaluation-aod-cut-balance
  results: []
---

<!-- 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-large-xlsr-53-english-pronunciation-evaluation-aod-cut-balance

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0674
- Accuracy: 0.6055
- F1: 0.6017
- Precision: 0.6074
- Recall: 0.6055

## 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: 8
- 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_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0011        | 1.0   | 105  | 1.0494          | 0.5      | 0.4111 | 0.4721    | 0.5    |
| 0.7777        | 2.0   | 210  | 0.9454          | 0.5576   | 0.5178 | 0.5332    | 0.5576 |
| 0.7462        | 3.0   | 315  | 1.1190          | 0.5815   | 0.5649 | 0.5757    | 0.5815 |
| 0.6099        | 4.0   | 420  | 1.0299          | 0.6043   | 0.5975 | 0.5992    | 0.6043 |
| 0.4457        | 5.0   | 525  | 1.0674          | 0.6055   | 0.6017 | 0.6074    | 0.6055 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3