README.md

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: []
datasets:
  - DL-Project/DL_Audio_Hatespeech_Dataset
language:
  - en

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

It achieves the following results on the test set:

• Loss: 0.6597
• Accuracy: 0.6192
• Recall: 0.7822
• Precision: 0.5944
• F1: 0.6755

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