hatespeech_wav2vec2 / README.md
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wav2vec finetuning on full dataset
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - recall
  - precision
  - f1
model-index:
  - name: DL_Audio_Hatespeech_wav2vec_trainer_push
    results: []

DL_Audio_Hatespeech_wav2vec_trainer_push

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6562
  • Accuracy: 0.6216
  • Recall: 0.7853
  • Precision: 0.5990
  • F1: 0.6796

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: 4e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Recall Precision F1
No log 0.9935 77 0.6871 0.5430 0.9021 0.5311 0.6686
0.6899 2.0 155 0.6779 0.5647 0.9021 0.5448 0.6793
0.6761 2.9935 232 0.6649 0.5934 0.5541 0.6131 0.5821
0.6607 4.0 310 0.6550 0.6289 0.6504 0.6334 0.6417
0.6607 4.9935 387 0.6562 0.6216 0.7853 0.5990 0.6796
0.6403 6.0 465 0.6578 0.6357 0.6969 0.6298 0.6617
0.6129 6.9935 542 0.6623 0.6313 0.7277 0.6184 0.6686
0.6024 8.0 620 0.6745 0.6345 0.7490 0.6174 0.6769
0.5779 8.9935 697 0.6807 0.6406 0.6567 0.6460 0.6513
0.5779 9.9355 770 0.6798 0.6337 0.6993 0.6270 0.6612

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1