---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
  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-base-finetuned-ks

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6810
- Accuracy: 0.6471

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 500
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 0.6810          | 0.6471   |
| 0.6835        | 2.0   | 10   | 0.6785          | 0.6471   |
| 0.6835        | 3.0   | 15   | 0.6748          | 0.6471   |
| 0.6745        | 4.0   | 20   | 0.6715          | 0.6471   |
| 0.6745        | 5.0   | 25   | 0.6688          | 0.6471   |
| 0.6773        | 6.0   | 30   | 0.6622          | 0.6471   |
| 0.6773        | 7.0   | 35   | 0.6585          | 0.6471   |
| 0.6663        | 8.0   | 40   | 0.6553          | 0.6471   |
| 0.6663        | 9.0   | 45   | 0.6539          | 0.6471   |
| 0.6254        | 10.0  | 50   | 0.6514          | 0.6471   |
| 0.6254        | 11.0  | 55   | 0.6506          | 0.6471   |
| 0.6697        | 12.0  | 60   | 0.6498          | 0.6471   |
| 0.6697        | 13.0  | 65   | 0.6604          | 0.6471   |
| 0.6485        | 14.0  | 70   | 0.6556          | 0.6471   |
| 0.6485        | 15.0  | 75   | 0.6504          | 0.6471   |
| 0.6802        | 16.0  | 80   | 0.6636          | 0.6471   |
| 0.6802        | 17.0  | 85   | 0.6521          | 0.6471   |
| 0.6737        | 18.0  | 90   | 0.6494          | 0.6471   |
| 0.6737        | 19.0  | 95   | 0.6494          | 0.6471   |
| 0.6687        | 20.0  | 100  | 0.6493          | 0.6471   |
| 0.6687        | 21.0  | 105  | 0.6500          | 0.6471   |
| 0.6456        | 22.0  | 110  | 0.6500          | 0.6471   |
| 0.6456        | 23.0  | 115  | 0.6493          | 0.6471   |
| 0.6448        | 24.0  | 120  | 0.6493          | 0.6471   |
| 0.6448        | 25.0  | 125  | 0.6495          | 0.6471   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2