---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: w2v2-ks-jpqd-lr1e-4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v2-ks-jpqd-lr1e-4

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: 0.1228
- Accuracy: 0.9695

## 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: 32
- eval_batch_size: 64
- 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: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5357        | 1.0   | 399  | 2.7821          | 0.6209   |
| 2.7107        | 2.0   | 798  | 2.7331          | 0.6209   |
| 2.671         | 3.0   | 1197 | 2.7330          | 0.6209   |
| 14.208        | 4.0   | 1596 | 14.2660         | 0.7139   |
| 21.0916       | 5.0   | 1995 | 21.0315         | 0.8104   |
| 24.4471       | 6.0   | 2394 | 24.2357         | 0.9073   |
| 25.366        | 7.0   | 2793 | 25.0893         | 0.9273   |
| 25.1369       | 8.0   | 3192 | 24.8976         | 0.9394   |
| 0.4678        | 9.0   | 3591 | 0.2528          | 0.9435   |
| 0.3576        | 10.0  | 3990 | 0.1873          | 0.9613   |
| 0.3622        | 11.0  | 4389 | 0.1583          | 0.9645   |
| 0.2796        | 12.0  | 4788 | 0.1419          | 0.9666   |
| 0.3157        | 13.0  | 5187 | 0.1327          | 0.9693   |
| 0.2997        | 14.0  | 5586 | 0.1263          | 0.9694   |
| 0.2667        | 15.0  | 5985 | 0.1228          | 0.9695   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2