---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: wav2vec2-base-960h-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-960h-finetuned-ks

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9308
- Accuracy: 0.7752
- F1: 0.7749

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.3739        | 0.99  | 35   | 1.3646          | 0.3654   | 0.2858 |
| 1.3444        | 2.0   | 71   | 1.3366          | 0.3833   | 0.3172 |
| 1.3193        | 2.99  | 106  | 1.2654          | 0.4324   | 0.3350 |
| 1.2447        | 4.0   | 142  | 1.2093          | 0.4649   | 0.3611 |
| 1.2087        | 4.99  | 177  | 1.2030          | 0.4582   | 0.3714 |
| 1.1539        | 6.0   | 213  | 1.1419          | 0.4920   | 0.4317 |
| 1.0795        | 6.99  | 248  | 1.1794          | 0.4721   | 0.4207 |
| 1.0525        | 8.0   | 284  | 1.0922          | 0.5020   | 0.4684 |
| 1.0615        | 8.99  | 319  | 1.0459          | 0.5471   | 0.5158 |
| 0.9381        | 10.0  | 355  | 1.0080          | 0.5656   | 0.5464 |
| 0.8945        | 10.99 | 390  | 1.1166          | 0.5378   | 0.5108 |
| 0.8497        | 12.0  | 426  | 1.0068          | 0.5855   | 0.5772 |
| 0.7729        | 12.99 | 461  | 1.1214          | 0.5517   | 0.5406 |
| 0.6984        | 14.0  | 497  | 1.0416          | 0.5889   | 0.5729 |
| 0.6856        | 14.99 | 532  | 1.0135          | 0.6180   | 0.6185 |
| 0.6095        | 16.0  | 568  | 1.0088          | 0.6320   | 0.6299 |
| 0.5899        | 16.99 | 603  | 0.9208          | 0.6585   | 0.6612 |
| 0.5922        | 18.0  | 639  | 0.8657          | 0.6757   | 0.6749 |
| 0.537         | 18.99 | 674  | 0.8910          | 0.6850   | 0.6892 |
| 0.4767        | 20.0  | 710  | 1.0544          | 0.6525   | 0.6499 |
| 0.4864        | 20.99 | 745  | 0.8024          | 0.7255   | 0.7232 |
| 0.3546        | 22.0  | 781  | 0.8628          | 0.7168   | 0.7205 |
| 0.3567        | 22.99 | 816  | 0.8921          | 0.7168   | 0.7177 |
| 0.381         | 24.0  | 852  | 0.9130          | 0.7069   | 0.7081 |
| 0.3031        | 24.99 | 887  | 1.0026          | 0.7023   | 0.7039 |
| 0.412         | 26.0  | 923  | 0.8413          | 0.7420   | 0.7430 |
| 0.3175        | 26.99 | 958  | 0.8705          | 0.7294   | 0.7335 |
| 0.2581        | 28.0  | 994  | 0.8628          | 0.7387   | 0.7431 |
| 0.328         | 28.99 | 1029 | 0.9022          | 0.7414   | 0.7417 |
| 0.263         | 30.0  | 1065 | 0.9787          | 0.7248   | 0.7251 |
| 0.249         | 30.99 | 1100 | 0.8658          | 0.7454   | 0.7481 |
| 0.2242        | 32.0  | 1136 | 0.9386          | 0.7354   | 0.7380 |
| 0.2848        | 32.99 | 1171 | 0.8553          | 0.7633   | 0.7639 |
| 0.2457        | 34.0  | 1207 | 0.8789          | 0.7692   | 0.7674 |
| 0.1557        | 34.99 | 1242 | 0.8542          | 0.7553   | 0.7594 |
| 0.169         | 36.0  | 1278 | 0.9132          | 0.7573   | 0.7600 |
| 0.171         | 36.99 | 1313 | 0.9550          | 0.7467   | 0.7481 |
| 0.2209        | 38.0  | 1349 | 0.9843          | 0.7407   | 0.7408 |
| 0.1674        | 38.99 | 1384 | 0.9523          | 0.7460   | 0.7468 |
| 0.1998        | 40.0  | 1420 | 0.8683          | 0.7686   | 0.7697 |
| 0.1101        | 40.99 | 1455 | 1.0123          | 0.7354   | 0.7370 |
| 0.1466        | 42.0  | 1491 | 0.9332          | 0.7633   | 0.7651 |
| 0.1376        | 42.99 | 1526 | 0.9193          | 0.7739   | 0.7743 |
| 0.0939        | 44.0  | 1562 | 0.9234          | 0.7626   | 0.7634 |
| 0.1333        | 44.99 | 1597 | 0.9308          | 0.7752   | 0.7749 |
| 0.1183        | 46.0  | 1633 | 0.9375          | 0.7706   | 0.7712 |
| 0.1031        | 46.99 | 1668 | 0.9298          | 0.7739   | 0.7750 |
| 0.1154        | 48.0  | 1704 | 0.9373          | 0.7739   | 0.7745 |
| 0.1317        | 48.99 | 1739 | 0.9611          | 0.7646   | 0.7654 |
| 0.1132        | 49.3  | 1750 | 0.9606          | 0.7626   | 0.7635 |


### Framework versions

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