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---
base_model: Harveenchadha/vakyansh-wav2vec2-malayalam-mlm-8
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vakyansh-wav2vec2-malayalam-mlm-8-audio-abuse-feature
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. -->
# vakyansh-wav2vec2-malayalam-mlm-8-audio-abuse-feature
This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-malayalam-mlm-8](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-malayalam-mlm-8) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5558
- Accuracy: 0.8118
- Macro F1-score: 0.7576
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 6.7625 | 0.77 | 10 | 6.7667 | 0.0 | 0.0 |
| 6.6935 | 1.54 | 20 | 6.5968 | 0.2527 | 0.0191 |
| 6.5445 | 2.31 | 30 | 6.3912 | 0.6909 | 0.4086 |
| 6.338 | 3.08 | 40 | 6.0995 | 0.6909 | 0.4086 |
| 6.1044 | 3.85 | 50 | 5.7554 | 0.6909 | 0.4086 |
| 5.755 | 4.62 | 60 | 5.4099 | 0.6909 | 0.4086 |
| 5.4695 | 5.38 | 70 | 5.1276 | 0.6909 | 0.4086 |
| 5.1723 | 6.15 | 80 | 4.8795 | 0.6909 | 0.4086 |
| 4.9648 | 6.92 | 90 | 4.6629 | 0.6909 | 0.4086 |
| 4.7414 | 7.69 | 100 | 4.4481 | 0.6909 | 0.4086 |
| 4.5793 | 8.46 | 110 | 4.2398 | 0.6909 | 0.4086 |
| 4.4455 | 9.23 | 120 | 4.0339 | 0.6909 | 0.4086 |
| 4.2287 | 10.0 | 130 | 3.8247 | 0.6909 | 0.4086 |
| 3.9367 | 10.77 | 140 | 3.6164 | 0.6909 | 0.4086 |
| 3.7916 | 11.54 | 150 | 3.4090 | 0.6909 | 0.4086 |
| 3.6112 | 12.31 | 160 | 3.2043 | 0.6909 | 0.4086 |
| 3.408 | 13.08 | 170 | 3.0023 | 0.6909 | 0.4086 |
| 3.1359 | 13.85 | 180 | 2.8029 | 0.6909 | 0.4086 |
| 2.9607 | 14.62 | 190 | 2.6125 | 0.6909 | 0.4086 |
| 2.83 | 15.38 | 200 | 2.4336 | 0.6909 | 0.4086 |
| 2.4853 | 16.15 | 210 | 2.2649 | 0.6909 | 0.4086 |
| 2.3841 | 16.92 | 220 | 2.1059 | 0.6909 | 0.4086 |
| 2.2296 | 17.69 | 230 | 1.9583 | 0.6909 | 0.4086 |
| 1.9631 | 18.46 | 240 | 1.8302 | 0.6909 | 0.4086 |
| 2.0456 | 19.23 | 250 | 1.7146 | 0.6909 | 0.4086 |
| 1.8406 | 20.0 | 260 | 1.6100 | 0.6909 | 0.4086 |
| 1.7127 | 20.77 | 270 | 1.5130 | 0.6909 | 0.4086 |
| 1.5241 | 21.54 | 280 | 1.4264 | 0.6909 | 0.4086 |
| 1.4366 | 22.31 | 290 | 1.3458 | 0.6909 | 0.4086 |
| 1.4368 | 23.08 | 300 | 1.2710 | 0.6909 | 0.4086 |
| 1.2664 | 23.85 | 310 | 1.2024 | 0.6909 | 0.4086 |
| 1.2681 | 24.62 | 320 | 1.1391 | 0.6909 | 0.4086 |
| 1.1518 | 25.38 | 330 | 1.0791 | 0.6909 | 0.4086 |
| 1.0681 | 26.15 | 340 | 1.0221 | 0.6909 | 0.4086 |
| 1.014 | 26.92 | 350 | 0.9679 | 0.6909 | 0.4086 |
| 0.9918 | 27.69 | 360 | 0.9197 | 0.6909 | 0.4086 |
| 1.0046 | 28.46 | 370 | 0.8839 | 0.6909 | 0.4086 |
| 0.9582 | 29.23 | 380 | 0.8422 | 0.6909 | 0.4086 |
| 0.927 | 30.0 | 390 | 0.8017 | 0.6909 | 0.4086 |
| 0.8853 | 30.77 | 400 | 0.7666 | 0.6909 | 0.4086 |
| 0.7872 | 31.54 | 410 | 0.7353 | 0.6909 | 0.4086 |
| 0.7773 | 32.31 | 420 | 0.7032 | 0.6909 | 0.4086 |
| 0.7163 | 33.08 | 430 | 0.6929 | 0.6909 | 0.4086 |
| 0.7686 | 33.85 | 440 | 0.6617 | 0.6909 | 0.4086 |
| 0.7504 | 34.62 | 450 | 0.6623 | 0.6909 | 0.4086 |
| 0.7491 | 35.38 | 460 | 0.6333 | 0.6909 | 0.4086 |
| 0.6688 | 36.15 | 470 | 0.6115 | 0.6962 | 0.4348 |
| 0.6785 | 36.92 | 480 | 0.5968 | 0.6909 | 0.4086 |
| 0.6511 | 37.69 | 490 | 0.5879 | 0.6909 | 0.4086 |
| 0.5906 | 38.46 | 500 | 0.5855 | 0.8253 | 0.7679 |
| 0.6 | 39.23 | 510 | 0.5837 | 0.8065 | 0.7299 |
| 0.604 | 40.0 | 520 | 0.5683 | 0.8226 | 0.7699 |
| 0.6269 | 40.77 | 530 | 0.5697 | 0.8065 | 0.7362 |
| 0.5643 | 41.54 | 540 | 0.5628 | 0.8199 | 0.7687 |
| 0.6269 | 42.31 | 550 | 0.5650 | 0.8145 | 0.7570 |
| 0.5965 | 43.08 | 560 | 0.5666 | 0.8065 | 0.7473 |
| 0.5578 | 43.85 | 570 | 0.5683 | 0.8065 | 0.7401 |
| 0.5571 | 44.62 | 580 | 0.5607 | 0.8172 | 0.7690 |
| 0.5511 | 45.38 | 590 | 0.5566 | 0.8145 | 0.7618 |
| 0.5404 | 46.15 | 600 | 0.5587 | 0.8091 | 0.7482 |
| 0.5708 | 46.92 | 610 | 0.5541 | 0.8172 | 0.7660 |
| 0.62 | 47.69 | 620 | 0.5524 | 0.8145 | 0.7618 |
| 0.6095 | 48.46 | 630 | 0.5573 | 0.8065 | 0.7438 |
| 0.5282 | 49.23 | 640 | 0.5559 | 0.8145 | 0.7586 |
| 0.5307 | 50.0 | 650 | 0.5558 | 0.8118 | 0.7576 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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