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roberta_comp
This model is a fine-tuned version of ibm/ColD-Fusion on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3066
- F1: 0.8077
- Roc Auc: 0.8650
- Accuracy: 0.5765
- Recall: 0.8105
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 231 | 0.3455 | 0.7594 | 0.8284 | 0.5306 | 0.7474 |
| No log | 2.0 | 462 | 0.2986 | 0.7986 | 0.8569 | 0.5714 | 0.7930 |
| 0.3143 | 3.0 | 693 | 0.3006 | 0.8056 | 0.8632 | 0.5867 | 0.8070 |
| 0.3143 | 4.0 | 924 | 0.3066 | 0.8077 | 0.8650 | 0.5765 | 0.8105 |
| 0.1365 | 5.0 | 1155 | 0.3117 | 0.8028 | 0.8618 | 0.5663 | 0.8070 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+rocm5.2
- Datasets 2.8.0
- Tokenizers 0.13.2
