CS221-roberta-base-finetuned-semeval
This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4034
- F1: 0.7691
- Roc Auc: 0.8290
- Accuracy: 0.4693
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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
---|---|---|---|---|---|---|
0.4771 | 1.0 | 139 | 0.4703 | 0.6415 | 0.7338 | 0.2726 |
0.3912 | 2.0 | 278 | 0.3851 | 0.7136 | 0.7832 | 0.4152 |
0.2926 | 3.0 | 417 | 0.3753 | 0.7356 | 0.8007 | 0.4296 |
0.2346 | 4.0 | 556 | 0.3926 | 0.7517 | 0.8140 | 0.4513 |
0.1668 | 5.0 | 695 | 0.4034 | 0.7691 | 0.8290 | 0.4693 |
0.1126 | 6.0 | 834 | 0.3952 | 0.7633 | 0.8198 | 0.4838 |
0.0954 | 7.0 | 973 | 0.4348 | 0.7512 | 0.8116 | 0.4368 |
0.068 | 8.0 | 1112 | 0.4646 | 0.7499 | 0.8120 | 0.4495 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for Kuongan/CS221-roberta-base-finetuned-semeval
Base model
FacebookAI/roberta-base