---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
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: 1.1376
- Accuracy: 0.8210
- F1: 0.8209

## 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: 42
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.3731        | 0.99  | 35   | 1.3532          | 0.3767   | 0.2859 |
| 1.3039        | 2.0   | 71   | 1.2740          | 0.4237   | 0.3434 |
| 1.2185        | 2.99  | 106  | 1.1573          | 0.5020   | 0.4423 |
| 1.0887        | 4.0   | 142  | 1.1107          | 0.5013   | 0.4389 |
| 1.0183        | 4.99  | 177  | 1.0801          | 0.5610   | 0.5348 |
| 0.8625        | 6.0   | 213  | 0.9364          | 0.6373   | 0.6285 |
| 0.7487        | 6.99  | 248  | 0.9735          | 0.6048   | 0.5867 |
| 0.6151        | 8.0   | 284  | 0.8946          | 0.6698   | 0.6735 |
| 0.5081        | 8.99  | 319  | 0.8748          | 0.6797   | 0.6855 |
| 0.4559        | 10.0  | 355  | 0.8701          | 0.6850   | 0.6832 |
| 0.4347        | 10.99 | 390  | 0.8887          | 0.7003   | 0.7040 |
| 0.2845        | 12.0  | 426  | 0.8715          | 0.7129   | 0.7145 |
| 0.275         | 12.99 | 461  | 0.8846          | 0.7268   | 0.7263 |
| 0.2301        | 14.0  | 497  | 0.8651          | 0.7261   | 0.7324 |
| 0.1657        | 14.99 | 532  | 0.8573          | 0.7473   | 0.7473 |
| 0.1593        | 16.0  | 568  | 0.8472          | 0.7420   | 0.7443 |
| 0.1398        | 16.99 | 603  | 0.7433          | 0.7825   | 0.7829 |
| 0.1318        | 18.0  | 639  | 0.7989          | 0.7739   | 0.7768 |
| 0.1425        | 18.99 | 674  | 0.7967          | 0.7759   | 0.7788 |
| 0.1116        | 20.0  | 710  | 0.8969          | 0.7659   | 0.7650 |
| 0.0716        | 20.99 | 745  | 0.9783          | 0.7434   | 0.7480 |
| 0.0909        | 22.0  | 781  | 0.9413          | 0.7593   | 0.7626 |
| 0.0691        | 22.99 | 816  | 0.9298          | 0.7832   | 0.7832 |
| 0.068         | 24.0  | 852  | 0.9522          | 0.7725   | 0.7744 |
| 0.0416        | 24.99 | 887  | 0.9624          | 0.7686   | 0.7746 |
| 0.0569        | 26.0  | 923  | 0.9376          | 0.7832   | 0.7832 |
| 0.0369        | 26.99 | 958  | 1.0163          | 0.7845   | 0.7843 |
| 0.0482        | 28.0  | 994  | 1.0013          | 0.7931   | 0.7895 |
| 0.0497        | 28.99 | 1029 | 1.1005          | 0.7725   | 0.7713 |
| 0.0427        | 30.0  | 1065 | 1.0346          | 0.7891   | 0.7901 |
| 0.0252        | 30.99 | 1100 | 1.0611          | 0.7871   | 0.7883 |
| 0.0268        | 32.0  | 1136 | 1.0436          | 0.7944   | 0.7962 |
| 0.022         | 32.99 | 1171 | 1.0217          | 0.8031   | 0.8012 |
| 0.0127        | 34.0  | 1207 | 1.0936          | 0.7971   | 0.7969 |
| 0.0153        | 34.99 | 1242 | 1.0777          | 0.8097   | 0.8055 |
| 0.0062        | 36.0  | 1278 | 1.2379          | 0.7699   | 0.7751 |
| 0.0081        | 36.99 | 1313 | 1.0697          | 0.7977   | 0.7987 |
| 0.0072        | 38.0  | 1349 | 1.1284          | 0.7997   | 0.8001 |
| 0.0105        | 38.99 | 1384 | 1.0593          | 0.8137   | 0.8136 |
| 0.0102        | 40.0  | 1420 | 1.0805          | 0.8130   | 0.8126 |
| 0.0088        | 40.99 | 1455 | 1.1237          | 0.8110   | 0.8115 |
| 0.0073        | 42.0  | 1491 | 1.0980          | 0.8170   | 0.8167 |
| 0.0046        | 42.99 | 1526 | 1.1584          | 0.8044   | 0.8049 |
| 0.0061        | 44.0  | 1562 | 1.1517          | 0.8110   | 0.8114 |
| 0.0021        | 44.99 | 1597 | 1.1564          | 0.8064   | 0.8074 |
| 0.0073        | 46.0  | 1633 | 1.1214          | 0.8183   | 0.8183 |
| 0.002         | 46.99 | 1668 | 1.1376          | 0.8210   | 0.8209 |
| 0.0064        | 48.0  | 1704 | 1.1283          | 0.8210   | 0.8208 |
| 0.0072        | 48.99 | 1739 | 1.1271          | 0.8203   | 0.8201 |
| 0.0019        | 49.3  | 1750 | 1.1273          | 0.8203   | 0.8201 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0