RoBERTa_Combined_Generated_epoch_8
This model is a fine-tuned version of ICT2214Team7/RoBERTa_Test_Training on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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: 5e-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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 200 | 0.0071 | 0.9859 | 0.9899 | 0.9879 | 0.9984 |
No log | 2.0 | 400 | 0.0022 | 0.9939 | 0.9939 | 0.9939 | 0.9993 |
0.0735 | 3.0 | 600 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0735 | 4.0 | 800 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0024 | 5.0 | 1000 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0024 | 6.0 | 1200 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0024 | 7.0 | 1400 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0007 | 8.0 | 1600 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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