
<!-- 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. -->

# vakyansh-wav2vec2-kannada-knm-560-audio-abuse-feature

This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-kannada-knm-560](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-kannada-knm-560) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6403
- Accuracy: 0.7100
- Macro F1-score: 0.6596

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 | Macro F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 6.6756        | 0.77  | 10   | 6.6487          | 0.0      | 0.0            |
| 6.6336        | 1.54  | 20   | 6.5448          | 0.5474   | 0.0647         |
| 6.4999        | 2.31  | 30   | 6.3245          | 0.6585   | 0.3971         |
| 6.2688        | 3.08  | 40   | 6.0120          | 0.6585   | 0.3971         |
| 6.0598        | 3.85  | 50   | 5.7401          | 0.6585   | 0.3971         |
| 5.7739        | 4.62  | 60   | 5.4859          | 0.6585   | 0.3971         |
| 5.5736        | 5.38  | 70   | 5.2443          | 0.6585   | 0.3971         |
| 5.3092        | 6.15  | 80   | 5.0361          | 0.6585   | 0.3971         |
| 5.1088        | 6.92  | 90   | 4.8282          | 0.6585   | 0.3971         |
| 4.9566        | 7.69  | 100  | 4.6295          | 0.6585   | 0.3971         |
| 4.7528        | 8.46  | 110  | 4.4350          | 0.6585   | 0.3971         |
| 4.6942        | 9.23  | 120  | 4.2479          | 0.6585   | 0.3971         |
| 4.4164        | 10.0  | 130  | 4.0578          | 0.6585   | 0.3971         |
| 4.1989        | 10.77 | 140  | 3.8571          | 0.6585   | 0.3971         |
| 4.0312        | 11.54 | 150  | 3.6581          | 0.6585   | 0.3971         |
| 3.8758        | 12.31 | 160  | 3.4561          | 0.6585   | 0.3971         |
| 3.7026        | 13.08 | 170  | 3.2569          | 0.6585   | 0.3971         |
| 3.4173        | 13.85 | 180  | 3.0592          | 0.6585   | 0.3971         |
| 3.2018        | 14.62 | 190  | 2.8633          | 0.6585   | 0.3971         |
| 3.1789        | 15.38 | 200  | 2.6746          | 0.6585   | 0.3971         |
| 2.8636        | 16.15 | 210  | 2.4860          | 0.6585   | 0.3971         |
| 2.6381        | 16.92 | 220  | 2.3059          | 0.6585   | 0.3971         |
| 2.5071        | 17.69 | 230  | 2.1303          | 0.6585   | 0.3971         |
| 2.2478        | 18.46 | 240  | 1.9669          | 0.6585   | 0.3971         |
| 2.2718        | 19.23 | 250  | 1.8162          | 0.6585   | 0.3971         |
| 2.0259        | 20.0  | 260  | 1.6750          | 0.6585   | 0.3971         |
| 1.8823        | 20.77 | 270  | 1.5460          | 0.6585   | 0.3971         |
| 1.6591        | 21.54 | 280  | 1.4290          | 0.6585   | 0.3971         |
| 1.5646        | 22.31 | 290  | 1.3213          | 0.6585   | 0.3971         |
| 1.487         | 23.08 | 300  | 1.2263          | 0.6585   | 0.3971         |
| 1.3681        | 23.85 | 310  | 1.1424          | 0.6585   | 0.3971         |
| 1.2941        | 24.62 | 320  | 1.0696          | 0.6585   | 0.3971         |
| 1.1374        | 25.38 | 330  | 1.0059          | 0.6585   | 0.3971         |
| 1.0881        | 26.15 | 340  | 0.9470          | 0.6585   | 0.3971         |
| 0.9892        | 26.92 | 350  | 0.8987          | 0.6585   | 0.3971         |
| 1.0156        | 27.69 | 360  | 0.8547          | 0.6585   | 0.3971         |
| 0.9592        | 28.46 | 370  | 0.8181          | 0.6585   | 0.3971         |
| 0.937         | 29.23 | 380  | 0.7861          | 0.6585   | 0.3971         |
| 0.8938        | 30.0  | 390  | 0.7572          | 0.6585   | 0.3971         |
| 0.8651        | 30.77 | 400  | 0.7331          | 0.6585   | 0.3971         |
| 0.8051        | 31.54 | 410  | 0.7182          | 0.6585   | 0.3971         |
| 0.7774        | 32.31 | 420  | 0.7072          | 0.6585   | 0.3971         |
| 0.749         | 33.08 | 430  | 0.6787          | 0.6585   | 0.3971         |
| 0.7762        | 33.85 | 440  | 0.6687          | 0.6585   | 0.3971         |
| 0.7223        | 34.62 | 450  | 0.6656          | 0.7480   | 0.6544         |
| 0.7363        | 35.38 | 460  | 0.6619          | 0.7534   | 0.6963         |
| 0.7039        | 36.15 | 470  | 0.6473          | 0.7371   | 0.6867         |
| 0.6923        | 36.92 | 480  | 0.6377          | 0.7453   | 0.6854         |
| 0.6667        | 37.69 | 490  | 0.6405          | 0.7317   | 0.6786         |
| 0.6419        | 38.46 | 500  | 0.6479          | 0.7127   | 0.6794         |
| 0.6511        | 39.23 | 510  | 0.6336          | 0.7344   | 0.6757         |
| 0.6638        | 40.0  | 520  | 0.6244          | 0.7236   | 0.6927         |
| 0.67          | 40.77 | 530  | 0.6241          | 0.7290   | 0.6795         |
| 0.616         | 41.54 | 540  | 0.6353          | 0.7182   | 0.6789         |
| 0.6592        | 42.31 | 550  | 0.6277          | 0.7344   | 0.6890         |
| 0.6146        | 43.08 | 560  | 0.6352          | 0.7236   | 0.6890         |
| 0.6103        | 43.85 | 570  | 0.6382          | 0.7100   | 0.6629         |
| 0.6099        | 44.62 | 580  | 0.6373          | 0.7100   | 0.6629         |
| 0.5724        | 45.38 | 590  | 0.6358          | 0.7182   | 0.6667         |
| 0.6134        | 46.15 | 600  | 0.6410          | 0.7073   | 0.6680         |
| 0.6084        | 46.92 | 610  | 0.6441          | 0.7127   | 0.6755         |
| 0.656         | 47.69 | 620  | 0.6400          | 0.7127   | 0.6727         |
| 0.6359        | 48.46 | 630  | 0.6405          | 0.7100   | 0.6689         |
| 0.5832        | 49.23 | 640  | 0.6407          | 0.7073   | 0.6621         |
| 0.5822        | 50.0  | 650  | 0.6403          | 0.7100   | 0.6596         |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "Harveenchadha/vakyansh-wav2vec2-kannada-knm-560", "model-index": [{"name": "vakyansh-wav2vec2-kannada-knm-560-audio-abuse-feature", "results": []}]}
transformers pytorch wav2vec2 audio-classification generated_from_trainer base_model:Harveenchadha/vakyansh-wav2vec2-kannada-knm-560 endpoints_compatible region:us