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roberta-similarity
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7067
- Accuracy: 0.832
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
---|---|---|---|---|
0.6376 | 0.16 | 10 | 0.6287 | 0.672 |
0.5909 | 0.32 | 20 | 0.5762 | 0.672 |
0.5422 | 0.48 | 30 | 0.6498 | 0.672 |
0.5876 | 0.63 | 40 | 0.6411 | 0.672 |
0.523 | 0.79 | 50 | 0.7330 | 0.67 |
0.5686 | 0.95 | 60 | 0.6911 | 0.672 |
0.4743 | 1.11 | 70 | 0.5254 | 0.792 |
0.4183 | 1.27 | 80 | 0.4998 | 0.818 |
0.3682 | 1.43 | 90 | 0.5912 | 0.816 |
0.6203 | 1.59 | 100 | 0.9526 | 0.706 |
0.5078 | 1.75 | 110 | 0.5348 | 0.824 |
0.3214 | 1.9 | 120 | 0.5120 | 0.816 |
0.3352 | 2.06 | 130 | 0.5275 | 0.808 |
0.2805 | 2.22 | 140 | 0.5597 | 0.816 |
0.2541 | 2.38 | 150 | 0.5253 | 0.83 |
0.3769 | 2.54 | 160 | 0.5075 | 0.796 |
0.3203 | 2.7 | 170 | 0.4701 | 0.816 |
0.2153 | 2.86 | 180 | 0.5483 | 0.814 |
0.1822 | 3.02 | 190 | 0.5819 | 0.832 |
0.1761 | 3.17 | 200 | 0.6913 | 0.822 |
0.301 | 3.33 | 210 | 0.7678 | 0.804 |
0.21 | 3.49 | 220 | 0.9464 | 0.798 |
0.3224 | 3.65 | 230 | 0.6209 | 0.832 |
0.133 | 3.81 | 240 | 0.7540 | 0.818 |
0.1826 | 3.97 | 250 | 0.7332 | 0.828 |
0.2547 | 4.13 | 260 | 0.6782 | 0.83 |
0.1321 | 4.29 | 270 | 0.7430 | 0.824 |
0.1661 | 4.44 | 280 | 0.8056 | 0.826 |
0.1525 | 4.6 | 290 | 0.6864 | 0.828 |
0.2085 | 4.76 | 300 | 0.6900 | 0.832 |
0.1201 | 4.92 | 310 | 0.7067 | 0.832 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3