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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- recall |
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- precision |
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- f1 |
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model-index: |
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- name: DL-Project/hatespeech_wav2vec2 |
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results: [] |
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datasets: |
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- DL-Project/DL_Audio_Hatespeech_Dataset |
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language: |
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- en |
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widget: |
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- src: example_hate.wav |
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example_title: Hate Speech Example |
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- src: example_non_hate.wav |
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example_title: Non-Hate Speech Example |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# hatespeech_wav2vec2 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6562 |
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- Accuracy: 0.6216 |
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- Recall: 0.7853 |
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- Precision: 0.5990 |
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- F1: 0.6796 |
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It achieves the following results on the test set: |
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- Loss: 0.6597 |
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- Accuracy: 0.6192 |
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- Recall: 0.7822 |
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- Precision: 0.5944 |
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- F1: 0.6755 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 0.9935 | 77 | 0.6871 | 0.5430 | 0.9021 | 0.5311 | 0.6686 | |
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| 0.6899 | 2.0 | 155 | 0.6779 | 0.5647 | 0.9021 | 0.5448 | 0.6793 | |
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| 0.6761 | 2.9935 | 232 | 0.6649 | 0.5934 | 0.5541 | 0.6131 | 0.5821 | |
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| 0.6607 | 4.0 | 310 | 0.6550 | 0.6289 | 0.6504 | 0.6334 | 0.6417 | |
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| 0.6607 | 4.9935 | 387 | 0.6562 | 0.6216 | 0.7853 | 0.5990 | 0.6796 | |
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| 0.6403 | 6.0 | 465 | 0.6578 | 0.6357 | 0.6969 | 0.6298 | 0.6617 | |
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| 0.6129 | 6.9935 | 542 | 0.6623 | 0.6313 | 0.7277 | 0.6184 | 0.6686 | |
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| 0.6024 | 8.0 | 620 | 0.6745 | 0.6345 | 0.7490 | 0.6174 | 0.6769 | |
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| 0.5779 | 8.9935 | 697 | 0.6807 | 0.6406 | 0.6567 | 0.6460 | 0.6513 | |
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| 0.5779 | 9.9355 | 770 | 0.6798 | 0.6337 | 0.6993 | 0.6270 | 0.6612 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
