transformers pytorch wav2vec2 audio-classification generated_from_trainer base_model:Harveenchadha/hindi_base_wav2vec2 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: Harveenchadha/hindi_base_wav2vec2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hindi_base_wav2vec2-audio-abuse-feature
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hindi_base_wav2vec2-audio-abuse-feature

This model is a fine-tuned version of [Harveenchadha/hindi_base_wav2vec2](https://huggingface.co/Harveenchadha/hindi_base_wav2vec2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7202
- Accuracy: 0.6694
- Macro F1-score: 0.6693

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 6.6553        | 0.77  | 10   | 6.6322          | 0.0      | 0.0            |
| 6.5758        | 1.54  | 20   | 6.4417          | 0.5447   | 0.2151         |
| 6.3599        | 2.31  | 30   | 6.1486          | 0.5122   | 0.3621         |
| 6.0708        | 3.08  | 40   | 5.7751          | 0.5041   | 0.3351         |
| 5.8361        | 3.85  | 50   | 5.4662          | 0.5041   | 0.3351         |
| 5.5167        | 4.62  | 60   | 5.2127          | 0.5041   | 0.3351         |
| 5.289         | 5.38  | 70   | 4.9640          | 0.5041   | 0.3351         |
| 5.0266        | 6.15  | 80   | 4.7282          | 0.5041   | 0.3351         |
| 4.78          | 6.92  | 90   | 4.5006          | 0.5041   | 0.3351         |
| 4.6197        | 7.69  | 100  | 4.2787          | 0.5041   | 0.3351         |
| 4.3798        | 8.46  | 110  | 4.0506          | 0.5041   | 0.3351         |
| 4.2651        | 9.23  | 120  | 3.8315          | 0.5041   | 0.3351         |
| 3.9832        | 10.0  | 130  | 3.6034          | 0.5041   | 0.3351         |
| 3.7163        | 10.77 | 140  | 3.3782          | 0.5041   | 0.3351         |
| 3.5481        | 11.54 | 150  | 3.1510          | 0.5041   | 0.3351         |
| 3.305         | 12.31 | 160  | 2.9279          | 0.5041   | 0.3351         |
| 3.1589        | 13.08 | 170  | 2.7102          | 0.5041   | 0.3351         |
| 2.8368        | 13.85 | 180  | 2.4942          | 0.5041   | 0.3351         |
| 2.5875        | 14.62 | 190  | 2.2896          | 0.5041   | 0.3351         |
| 2.5938        | 15.38 | 200  | 2.0940          | 0.5041   | 0.3351         |
| 2.2346        | 16.15 | 210  | 1.9083          | 0.5041   | 0.3351         |
| 2.0404        | 16.92 | 220  | 1.7372          | 0.5041   | 0.3351         |
| 1.8744        | 17.69 | 230  | 1.5755          | 0.5041   | 0.3351         |
| 1.6581        | 18.46 | 240  | 1.4332          | 0.5041   | 0.3351         |
| 1.7251        | 19.23 | 250  | 1.3152          | 0.5041   | 0.3351         |
| 1.4569        | 20.0  | 260  | 1.2093          | 0.5041   | 0.3351         |
| 1.3718        | 20.77 | 270  | 1.1160          | 0.5041   | 0.3351         |
| 1.1743        | 21.54 | 280  | 1.0209          | 0.5041   | 0.3351         |
| 1.0744        | 22.31 | 290  | 0.9585          | 0.6585   | 0.6309         |
| 1.0933        | 23.08 | 300  | 0.8902          | 0.7019   | 0.6941         |
| 0.9348        | 23.85 | 310  | 0.8504          | 0.6992   | 0.6940         |
| 0.9611        | 24.62 | 320  | 0.8094          | 0.6911   | 0.6901         |
| 0.8307        | 25.38 | 330  | 0.7750          | 0.6992   | 0.6992         |
| 0.7863        | 26.15 | 340  | 0.7776          | 0.6802   | 0.6724         |
| 0.7431        | 26.92 | 350  | 0.7624          | 0.6829   | 0.6737         |
| 0.7607        | 27.69 | 360  | 0.7450          | 0.6775   | 0.6747         |
| 0.8054        | 28.46 | 370  | 0.7161          | 0.6938   | 0.6914         |
| 0.752         | 29.23 | 380  | 0.7021          | 0.6965   | 0.6946         |
| 0.72          | 30.0  | 390  | 0.7060          | 0.6856   | 0.6846         |
| 0.7252        | 30.77 | 400  | 0.6968          | 0.6911   | 0.6910         |
| 0.6497        | 31.54 | 410  | 0.7016          | 0.6911   | 0.6905         |
| 0.6215        | 32.31 | 420  | 0.7209          | 0.6856   | 0.6848         |
| 0.6143        | 33.08 | 430  | 0.6941          | 0.6856   | 0.6856         |
| 0.6778        | 33.85 | 440  | 0.6887          | 0.6856   | 0.6850         |
| 0.6027        | 34.62 | 450  | 0.7010          | 0.6992   | 0.6990         |
| 0.6644        | 35.38 | 460  | 0.7009          | 0.6721   | 0.6674         |
| 0.6178        | 36.15 | 470  | 0.6840          | 0.7019   | 0.6985         |
| 0.5817        | 36.92 | 480  | 0.6974          | 0.6829   | 0.6827         |
| 0.5876        | 37.69 | 490  | 0.6914          | 0.6802   | 0.6801         |
| 0.5474        | 38.46 | 500  | 0.7056          | 0.6856   | 0.6855         |
| 0.5327        | 39.23 | 510  | 0.7128          | 0.6802   | 0.6800         |
| 0.5648        | 40.0  | 520  | 0.7067          | 0.6748   | 0.6730         |
| 0.6163        | 40.77 | 530  | 0.6804          | 0.6721   | 0.6721         |
| 0.514         | 41.54 | 540  | 0.6965          | 0.6775   | 0.6774         |
| 0.5817        | 42.31 | 550  | 0.7177          | 0.6775   | 0.6767         |
| 0.5345        | 43.08 | 560  | 0.7136          | 0.6775   | 0.6772         |
| 0.525         | 43.85 | 570  | 0.7159          | 0.6883   | 0.6876         |
| 0.5043        | 44.62 | 580  | 0.7110          | 0.6802   | 0.6801         |
| 0.5418        | 45.38 | 590  | 0.7149          | 0.6748   | 0.6746         |
| 0.5129        | 46.15 | 600  | 0.7108          | 0.6694   | 0.6694         |
| 0.5331        | 46.92 | 610  | 0.7118          | 0.6667   | 0.6667         |
| 0.6061        | 47.69 | 620  | 0.7248          | 0.6802   | 0.6795         |
| 0.5551        | 48.46 | 630  | 0.7196          | 0.6694   | 0.6694         |
| 0.5049        | 49.23 | 640  | 0.7190          | 0.6640   | 0.6638         |
| 0.4663        | 50.0  | 650  | 0.7202          | 0.6694   | 0.6693         |


### Framework versions

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