Hugging Face's logo

callmesan
/
vakyansh-wav2vec2-odia-orm-100-audio-abuse-feature

Audio Classification
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Community
vakyansh-wav2vec2-odia-orm-100-audio-abuse-feature / README.md
callmesan's picture
callmesan
End of training
e068b14 verified
preview code
|
raw
history blame
6.31 kB
metadata
base_model: Harveenchadha/vakyansh-wav2vec2-odia-orm-100
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: vakyansh-wav2vec2-odia-orm-100-audio-abuse-feature
    results: []

vakyansh-wav2vec2-odia-orm-100-audio-abuse-feature

This model is a fine-tuned version of Harveenchadha/vakyansh-wav2vec2-odia-orm-100 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7299
  • Accuracy: 0.7014
  • Macro F1-score: 0.6792

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
6.7078 0.78 10 6.6948 0.0 0.0
6.6539 1.57 20 6.5580 0.2 0.0342
6.5111 2.35 30 6.3377 0.5726 0.3641
6.268 3.14 40 6.0361 0.5726 0.3641
6.0748 3.92 50 5.7417 0.5726 0.3641
5.8205 4.71 60 5.4985 0.5726 0.3641
5.6051 5.49 70 5.2743 0.5726 0.3641
5.3589 6.27 80 5.0823 0.5726 0.3641
5.2019 7.06 90 4.8953 0.5726 0.3641
5.0528 7.84 100 4.7077 0.5726 0.3641
4.868 8.63 110 4.5244 0.5726 0.3641
4.7081 9.41 120 4.3347 0.5726 0.3641
4.437 10.2 130 4.1455 0.5726 0.3641
4.3225 10.98 140 3.9551 0.5726 0.3641
4.0945 11.76 150 3.7694 0.5726 0.3641
4.014 12.55 160 3.5710 0.5726 0.3641
3.8491 13.33 170 3.3814 0.5726 0.3641
3.4724 14.12 180 3.1873 0.5726 0.3641
3.2728 14.9 190 2.9999 0.5726 0.3641
3.1948 15.69 200 2.8224 0.5726 0.3641
2.9968 16.47 210 2.6368 0.5726 0.3641
2.6739 17.25 220 2.4462 0.5726 0.3641
2.561 18.04 230 2.2871 0.5726 0.3641
2.5101 18.82 240 2.1260 0.5726 0.3641
2.3307 19.61 250 1.9620 0.5726 0.3641
2.1022 20.39 260 1.8260 0.5726 0.3641
1.9909 21.18 270 1.6933 0.5726 0.3641
1.766 21.96 280 1.5644 0.5726 0.3641
1.7143 22.75 290 1.4669 0.5726 0.3641
1.5073 23.53 300 1.3482 0.5726 0.3641
1.6055 24.31 310 1.2643 0.5726 0.3641
1.321 25.1 320 1.1930 0.5726 0.3641
1.2165 25.88 330 1.1128 0.5726 0.3641
1.1484 26.67 340 1.0493 0.6712 0.6033
1.1413 27.45 350 0.9925 0.7096 0.6737
1.0462 28.24 360 0.9471 0.6877 0.6190
0.9667 29.02 370 0.9209 0.7123 0.6869
0.9918 29.8 380 0.8892 0.7205 0.6953
0.9112 30.59 390 0.8414 0.7123 0.6705
0.8666 31.37 400 0.8291 0.7123 0.6836
0.8096 32.16 410 0.8284 0.6959 0.6501
0.7987 32.94 420 0.7729 0.7425 0.7270
0.7529 33.73 430 0.7542 0.7260 0.7023
0.7605 34.51 440 0.7535 0.7260 0.7043
0.7011 35.29 450 0.7882 0.6959 0.6891
0.6868 36.08 460 0.7378 0.7260 0.7013
0.6858 36.86 470 0.7518 0.7096 0.6865
0.7546 37.65 480 0.7163 0.7342 0.7108
0.6717 38.43 490 0.7158 0.7397 0.7158
0.7048 39.22 500 0.7755 0.6575 0.6487
0.6767 40.0 510 0.7469 0.7068 0.6798
0.6621 40.78 520 0.7166 0.7205 0.7020
0.6639 41.57 530 0.7143 0.7151 0.6934
0.5988 42.35 540 0.7547 0.6767 0.6661
0.6179 43.14 550 0.7394 0.7014 0.6820
0.7033 43.92 560 0.7312 0.6986 0.6757
0.6076 44.71 570 0.7331 0.6904 0.6674
0.602 45.49 580 0.7341 0.6932 0.6718
0.545 46.27 590 0.7363 0.6932 0.6738
0.5881 47.06 600 0.7299 0.7014 0.6792

Framework versions

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