---
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: 0.3550
- Accuracy: 0.8727

## 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   | 8    | 0.6840          | 0.6      |
| 0.6867        | 2.0   | 16   | 0.6780          | 0.6364   |
| 0.6742        | 3.0   | 24   | 0.6601          | 0.6182   |
| 0.6446        | 4.0   | 32   | 0.6294          | 0.6364   |
| 0.6299        | 5.0   | 40   | 0.6002          | 0.6727   |
| 0.6299        | 6.0   | 48   | 0.5755          | 0.7091   |
| 0.6021        | 7.0   | 56   | 0.5530          | 0.7273   |
| 0.5678        | 8.0   | 64   | 0.5036          | 0.8182   |
| 0.5512        | 9.0   | 72   | 0.4753          | 0.8545   |
| 0.4784        | 10.0  | 80   | 0.4184          | 0.9273   |
| 0.4784        | 11.0  | 88   | 0.4102          | 0.8909   |
| 0.4515        | 12.0  | 96   | 0.4444          | 0.8182   |
| 0.4878        | 13.0  | 104  | 0.3780          | 0.9091   |
| 0.4418        | 14.0  | 112  | 0.4570          | 0.8      |
| 0.4746        | 15.0  | 120  | 0.3870          | 0.8545   |
| 0.4746        | 16.0  | 128  | 0.3932          | 0.8364   |
| 0.4226        | 17.0  | 136  | 0.2779          | 0.9636   |
| 0.4301        | 18.0  | 144  | 0.3125          | 0.9455   |
| 0.3482        | 19.0  | 152  | 0.3212          | 0.9091   |
| 0.3611        | 20.0  | 160  | 0.3925          | 0.8364   |
| 0.3611        | 21.0  | 168  | 0.3389          | 0.8909   |
| 0.3507        | 22.0  | 176  | 0.3099          | 0.8727   |
| 0.3241        | 23.0  | 184  | 0.3120          | 0.8727   |
| 0.2533        | 24.0  | 192  | 0.2313          | 0.9455   |
| 0.2466        | 25.0  | 200  | 0.3550          | 0.8727   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3