
<!-- 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-hindi-him-4200-audio-abuse-feature

This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-hindi-him-4200](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-hindi-him-4200) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6541
- Accuracy: 0.6938
- Macro F1-score: 0.6938

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 6.7199        | 0.77  | 10   | 6.7179          | 0.0      | 0.0            |
| 6.699         | 1.54  | 20   | 6.6606          | 0.1192   | 0.0134         |
| 6.6237        | 2.31  | 30   | 6.5410          | 0.4499   | 0.0852         |
| 6.4723        | 3.08  | 40   | 6.3277          | 0.5014   | 0.2226         |
| 6.2904        | 3.85  | 50   | 6.0526          | 0.5041   | 0.3351         |
| 6.0074        | 4.62  | 60   | 5.7219          | 0.5041   | 0.3351         |
| 5.7233        | 5.38  | 70   | 5.3914          | 0.5041   | 0.3351         |
| 5.4426        | 6.15  | 80   | 5.0902          | 0.5041   | 0.3351         |
| 5.1776        | 6.92  | 90   | 4.8584          | 0.5041   | 0.3351         |
| 5.0097        | 7.69  | 100  | 4.6328          | 0.5041   | 0.3351         |
| 4.7851        | 8.46  | 110  | 4.4098          | 0.5041   | 0.3351         |
| 4.6801        | 9.23  | 120  | 4.2064          | 0.5041   | 0.3351         |
| 4.4144        | 10.0  | 130  | 3.9980          | 0.5041   | 0.3351         |
| 4.1631        | 10.77 | 140  | 3.7914          | 0.5041   | 0.3351         |
| 4.0093        | 11.54 | 150  | 3.5793          | 0.5041   | 0.3351         |
| 3.7803        | 12.31 | 160  | 3.3708          | 0.5041   | 0.3351         |
| 3.645         | 13.08 | 170  | 3.1635          | 0.5041   | 0.3351         |
| 3.3334        | 13.85 | 180  | 2.9564          | 0.5041   | 0.3351         |
| 3.0942        | 14.62 | 190  | 2.7570          | 0.5041   | 0.3351         |
| 3.0844        | 15.38 | 200  | 2.5619          | 0.5041   | 0.3351         |
| 2.749         | 16.15 | 210  | 2.3733          | 0.5041   | 0.3351         |
| 2.5448        | 16.92 | 220  | 2.1896          | 0.5041   | 0.3351         |
| 2.3636        | 17.69 | 230  | 2.0160          | 0.5041   | 0.3351         |
| 2.1303        | 18.46 | 240  | 1.8579          | 0.5041   | 0.3351         |
| 2.1702        | 19.23 | 250  | 1.7136          | 0.5041   | 0.3351         |
| 1.8911        | 20.0  | 260  | 1.5809          | 0.5041   | 0.3351         |
| 1.7695        | 20.77 | 270  | 1.4511          | 0.5041   | 0.3351         |
| 1.5466        | 21.54 | 280  | 1.3433          | 0.5041   | 0.3351         |
| 1.4228        | 22.31 | 290  | 1.2479          | 0.5041   | 0.3351         |
| 1.4089        | 23.08 | 300  | 1.1632          | 0.5041   | 0.3351         |
| 1.2252        | 23.85 | 310  | 1.0900          | 0.5041   | 0.3351         |
| 1.2236        | 24.62 | 320  | 1.0268          | 0.5041   | 0.3351         |
| 1.0727        | 25.38 | 330  | 0.9742          | 0.5041   | 0.3351         |
| 1.0036        | 26.15 | 340  | 0.9273          | 0.5041   | 0.3351         |
| 0.95          | 26.92 | 350  | 0.8892          | 0.5041   | 0.3351         |
| 0.9304        | 27.69 | 360  | 0.8592          | 0.5041   | 0.3351         |
| 0.9426        | 28.46 | 370  | 0.8355          | 0.5041   | 0.3351         |
| 0.8967        | 29.23 | 380  | 0.8136          | 0.5041   | 0.3351         |
| 0.862         | 30.0  | 390  | 0.7942          | 0.5041   | 0.3351         |
| 0.8609        | 30.77 | 400  | 0.7799          | 0.5041   | 0.3351         |
| 0.8013        | 31.54 | 410  | 0.7667          | 0.5041   | 0.3351         |
| 0.7845        | 32.31 | 420  | 0.7572          | 0.5041   | 0.3351         |
| 0.77          | 33.08 | 430  | 0.7425          | 0.5041   | 0.3351         |
| 0.7952        | 33.85 | 440  | 0.7309          | 0.5041   | 0.3351         |
| 0.7433        | 34.62 | 450  | 0.7119          | 0.7046   | 0.7036         |
| 0.7791        | 35.38 | 460  | 0.7002          | 0.7019   | 0.6992         |
| 0.7409        | 36.15 | 470  | 0.6932          | 0.7073   | 0.7029         |
| 0.7233        | 36.92 | 480  | 0.6887          | 0.6911   | 0.6904         |
| 0.716         | 37.69 | 490  | 0.6820          | 0.6992   | 0.6986         |
| 0.6994        | 38.46 | 500  | 0.6821          | 0.6883   | 0.6881         |
| 0.6899        | 39.23 | 510  | 0.6701          | 0.6938   | 0.6930         |
| 0.7014        | 40.0  | 520  | 0.6683          | 0.6965   | 0.6965         |
| 0.7252        | 40.77 | 530  | 0.6632          | 0.7019   | 0.7011         |
| 0.6763        | 41.54 | 540  | 0.6650          | 0.6883   | 0.6882         |
| 0.7115        | 42.31 | 550  | 0.6615          | 0.6829   | 0.6829         |
| 0.6703        | 43.08 | 560  | 0.6628          | 0.6911   | 0.6908         |
| 0.6757        | 43.85 | 570  | 0.6626          | 0.6938   | 0.6935         |
| 0.6672        | 44.62 | 580  | 0.6545          | 0.7046   | 0.7043         |
| 0.6518        | 45.38 | 590  | 0.6559          | 0.6965   | 0.6965         |
| 0.6661        | 46.15 | 600  | 0.6610          | 0.6802   | 0.6800         |
| 0.679         | 46.92 | 610  | 0.6580          | 0.6856   | 0.6856         |
| 0.7079        | 47.69 | 620  | 0.6558          | 0.6911   | 0.6911         |
| 0.7103        | 48.46 | 630  | 0.6536          | 0.6992   | 0.6992         |
| 0.6613        | 49.23 | 640  | 0.6536          | 0.6965   | 0.6965         |
| 0.6326        | 50.0  | 650  | 0.6541          | 0.6938   | 0.6938         |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "Harveenchadha/vakyansh-wav2vec2-hindi-him-4200", "model-index": [{"name": "vakyansh-wav2vec2-hindi-him-4200-audio-abuse-feature", "results": []}]}
transformers pytorch wav2vec2 audio-classification generated_from_trainer base_model:Harveenchadha/vakyansh-wav2vec2-hindi-him-4200 license:mit endpoints_compatible region:us