roberta-base-hoeken2024hateful-random-augmented
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6422
- Accuracy: 0.7509
- Roc Auc: 0.8127
- Precision: 0.7077
- Recall: 0.7603
- F1: 0.7331
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: 96
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|---|
0.1579 | 1.0 | 902 | 1.2188 | 0.6952 | 0.8143 | 0.6127 | 0.8760 | 0.7211 |
0.0258 | 2.0 | 1804 | 1.3072 | 0.7361 | 0.8139 | 0.6667 | 0.8264 | 0.7380 |
0.0108 | 3.0 | 2706 | 1.6130 | 0.6989 | 0.8175 | 0.6149 | 0.8843 | 0.7254 |
0.0046 | 4.0 | 3608 | 1.6706 | 0.7435 | 0.8132 | 0.6857 | 0.7934 | 0.7356 |
0.0028 | 5.0 | 4510 | 1.6422 | 0.7509 | 0.8127 | 0.7077 | 0.7603 | 0.7331 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Base model
FacebookAI/roberta-base