transformers pytorch wav2vec2 audio-classification generated_from_trainer base_model:Harveenchadha/vakyansh-wav2vec2-gujarati-gnm-100 endpoints_compatible region:us
---
base_model: Harveenchadha/vakyansh-wav2vec2-gujarati-gnm-100
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vakyansh-wav2vec2-gujarati-gnm-100-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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# vakyansh-wav2vec2-gujarati-gnm-100-audio-abuse-feature

This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-gujarati-gnm-100](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-gujarati-gnm-100) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6313
- Accuracy: 0.7403
- Macro F1-score: 0.6830

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 6.6694        | 0.77  | 10   | 6.6451          | 0.0387   | 0.0021         |
| 6.6244        | 1.54  | 20   | 6.5275          | 0.6878   | 0.0694         |
| 6.4955        | 2.31  | 30   | 6.2972          | 0.7044   | 0.4133         |
| 6.2586        | 3.08  | 40   | 5.9826          | 0.7044   | 0.4133         |
| 6.044         | 3.85  | 50   | 5.6760          | 0.7044   | 0.4133         |
| 5.7859        | 4.62  | 60   | 5.3680          | 0.7044   | 0.4133         |
| 5.506         | 5.38  | 70   | 5.0967          | 0.7044   | 0.4133         |
| 5.2115        | 6.15  | 80   | 4.8565          | 0.7044   | 0.4133         |
| 5.0439        | 6.92  | 90   | 4.6328          | 0.7044   | 0.4133         |
| 4.924         | 7.69  | 100  | 4.4207          | 0.7044   | 0.4133         |
| 4.5905        | 8.46  | 110  | 4.2046          | 0.7044   | 0.4133         |
| 4.4629        | 9.23  | 120  | 3.9881          | 0.7044   | 0.4133         |
| 4.2224        | 10.0  | 130  | 3.7741          | 0.7044   | 0.4133         |
| 4.0429        | 10.77 | 140  | 3.5620          | 0.7044   | 0.4133         |
| 3.8484        | 11.54 | 150  | 3.3434          | 0.7044   | 0.4133         |
| 3.6943        | 12.31 | 160  | 3.1294          | 0.7044   | 0.4133         |
| 3.4667        | 13.08 | 170  | 2.9148          | 0.7044   | 0.4133         |
| 3.1164        | 13.85 | 180  | 2.7000          | 0.7044   | 0.4133         |
| 2.9152        | 14.62 | 190  | 2.4912          | 0.7044   | 0.4133         |
| 2.7946        | 15.38 | 200  | 2.2933          | 0.7044   | 0.4133         |
| 2.5293        | 16.15 | 210  | 2.1013          | 0.7044   | 0.4133         |
| 2.3488        | 16.92 | 220  | 1.9167          | 0.7044   | 0.4133         |
| 2.2396        | 17.69 | 230  | 1.7418          | 0.7044   | 0.4133         |
| 2.0293        | 18.46 | 240  | 1.5833          | 0.7044   | 0.4133         |
| 1.8431        | 19.23 | 250  | 1.4364          | 0.7044   | 0.4133         |
| 1.6658        | 20.0  | 260  | 1.3038          | 0.7044   | 0.4133         |
| 1.5557        | 20.77 | 270  | 1.1904          | 0.7044   | 0.4133         |
| 1.3412        | 21.54 | 280  | 1.0912          | 0.7044   | 0.4133         |
| 1.2984        | 22.31 | 290  | 0.9999          | 0.7044   | 0.4133         |
| 1.2517        | 23.08 | 300  | 0.9240          | 0.7044   | 0.4133         |
| 1.2419        | 23.85 | 310  | 0.8693          | 0.7044   | 0.4133         |
| 1.0371        | 24.62 | 320  | 0.8206          | 0.7044   | 0.4133         |
| 0.922         | 25.38 | 330  | 0.7805          | 0.7044   | 0.4133         |
| 0.8833        | 26.15 | 340  | 0.7281          | 0.7044   | 0.4133         |
| 0.9064        | 26.92 | 350  | 0.6964          | 0.7210   | 0.4922         |
| 0.7483        | 27.69 | 360  | 0.6807          | 0.7569   | 0.6771         |
| 0.7677        | 28.46 | 370  | 0.6561          | 0.7762   | 0.6848         |
| 0.7107        | 29.23 | 380  | 0.6450          | 0.7486   | 0.6847         |
| 0.7144        | 30.0  | 390  | 0.6669          | 0.7182   | 0.6808         |
| 0.6656        | 30.77 | 400  | 0.6288          | 0.7486   | 0.6764         |
| 0.6896        | 31.54 | 410  | 0.6029          | 0.7652   | 0.6635         |
| 0.6715        | 32.31 | 420  | 0.6152          | 0.7486   | 0.7021         |
| 0.6375        | 33.08 | 430  | 0.6008          | 0.7597   | 0.6966         |
| 0.6342        | 33.85 | 440  | 0.5941          | 0.7652   | 0.6892         |
| 0.5992        | 34.62 | 450  | 0.6102          | 0.7459   | 0.6879         |
| 0.623         | 35.38 | 460  | 0.5906          | 0.7652   | 0.6914         |
| 0.5489        | 36.15 | 470  | 0.5970          | 0.7624   | 0.6610         |
| 0.5553        | 36.92 | 480  | 0.6324          | 0.7320   | 0.6902         |
| 0.5514        | 37.69 | 490  | 0.5974          | 0.7514   | 0.6852         |
| 0.5342        | 38.46 | 500  | 0.6077          | 0.7541   | 0.6954         |
| 0.5337        | 39.23 | 510  | 0.6081          | 0.7514   | 0.6872         |
| 0.4809        | 40.0  | 520  | 0.6685          | 0.6961   | 0.6572         |
| 0.4985        | 40.77 | 530  | 0.6262          | 0.7348   | 0.6798         |
| 0.4888        | 41.54 | 540  | 0.6358          | 0.7403   | 0.6773         |
| 0.4737        | 42.31 | 550  | 0.6137          | 0.7624   | 0.6911         |
| 0.5249        | 43.08 | 560  | 0.6456          | 0.7293   | 0.6784         |
| 0.5049        | 43.85 | 570  | 0.6503          | 0.7210   | 0.6694         |
| 0.4927        | 44.62 | 580  | 0.6294          | 0.7348   | 0.6663         |
| 0.4553        | 45.38 | 590  | 0.6130          | 0.7541   | 0.6835         |
| 0.4631        | 46.15 | 600  | 0.6524          | 0.7238   | 0.6718         |
| 0.5969        | 46.92 | 610  | 0.6233          | 0.7431   | 0.6817         |
| 0.4679        | 47.69 | 620  | 0.6306          | 0.7403   | 0.6848         |
| 0.4932        | 48.46 | 630  | 0.6245          | 0.7486   | 0.6922         |
| 0.4723        | 49.23 | 640  | 0.6304          | 0.7431   | 0.6872         |
| 0.4636        | 50.0  | 650  | 0.6313          | 0.7403   | 0.6830         |


### Framework versions

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