---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: neunit-ks-ertong-chengren
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# neunit-ks-ertong-chengren

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0250
- Accuracy: 0.9937

## 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: 32
- eval_batch_size: 32
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1371        | 0.99  | 55   | 0.0927          | 0.9797   |
| 0.0421        | 2.0   | 111  | 0.0483          | 0.9899   |
| 0.0163        | 2.99  | 166  | 0.0473          | 0.9886   |
| 0.0101        | 4.0   | 222  | 0.0339          | 0.9899   |
| 0.0089        | 4.95  | 275  | 0.0250          | 0.9937   |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3