---
base_model: anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: testV4
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: superb
      type: superb
      config: ks
      split: validation
      args: ks
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6209179170344219
---

<!-- 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. -->

# testV4

This model is a fine-tuned version of [anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test](https://huggingface.co/anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9986
- Accuracy: 0.6209

## 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: 0
- 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: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.3236        | 1.0   | 100  | 1.9986          | 0.6209   |
| 1.6222        | 2.0   | 200  | 1.5412          | 0.6209   |
| 1.4879        | 3.0   | 300  | 1.5255          | 0.6209   |
| 1.4797        | 4.0   | 400  | 1.5182          | 0.6209   |
| 1.4761        | 5.0   | 500  | 1.5151          | 0.6209   |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2