---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xlsr-quality-daps
  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-quality-daps

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0289
- Accuracy: 0.9956

## 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: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6868        | 0.9630  | 13   | 0.6218          | 0.9595   |
| 0.6219        | 2.0     | 27   | 0.3568          | 0.9947   |
| 0.2823        | 2.9630  | 40   | 0.1729          | 0.9947   |
| 0.1789        | 4.0     | 54   | 0.0902          | 0.9947   |
| 0.1154        | 4.9630  | 67   | 0.0586          | 0.9952   |
| 0.063         | 6.0     | 81   | 0.0421          | 0.9960   |
| 0.0412        | 6.9630  | 94   | 0.0357          | 0.9960   |
| 0.0412        | 8.0     | 108  | 0.0395          | 0.9934   |
| 0.0376        | 8.9630  | 121  | 0.0312          | 0.9956   |
| 0.0248        | 10.0    | 135  | 0.0296          | 0.9960   |
| 0.0384        | 10.9630 | 148  | 0.0298          | 0.9952   |
| 0.0267        | 12.0    | 162  | 0.0319          | 0.9943   |
| 0.0244        | 12.9630 | 175  | 0.0307          | 0.9947   |
| 0.0197        | 14.0    | 189  | 0.0289          | 0.9956   |
| 0.023         | 14.4444 | 195  | 0.0289          | 0.9956   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.12.0
- Tokenizers 0.19.1