Imagination_binary
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7671
- Accuracy: 0.6002
- Precision: 0.6389
- Recall: 0.4589
- F1: 0.5341
- Auc: 0.6471
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: 32
- eval_batch_size: 32
- seed: 1234
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 118 | 0.6728 | 0.5890 | 0.5720 | 0.7032 | 0.6309 | 0.6367 |
| No log | 2.0 | 236 | 0.6567 | 0.6164 | 0.6054 | 0.6658 | 0.6342 | 0.6591 |
| No log | 3.0 | 354 | 0.6761 | 0.6152 | 0.6438 | 0.5137 | 0.5714 | 0.6659 |
| No log | 4.0 | 472 | 0.7671 | 0.6002 | 0.6389 | 0.4589 | 0.5341 | 0.6471 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1