scenario-KD-SCR-DIV2-data-glue-sst2-model-bert-base-uncased-run-3
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8394
- Accuracy: 0.8911
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: 32
- eval_batch_size: 32
- seed: 45
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6969
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.379 | 1.0 | 2105 | 1.9908 | 0.8784 |
0.8041 | 2.0 | 4210 | 1.6913 | 0.8865 |
0.6181 | 3.0 | 6315 | 1.9046 | 0.8784 |
0.4617 | 4.0 | 8420 | 1.6333 | 0.8922 |
0.41 | 5.0 | 10525 | 1.8034 | 0.8830 |
0.351 | 6.0 | 12630 | 1.8450 | 0.8899 |
0.32 | 7.0 | 14735 | 1.9411 | 0.8842 |
0.2927 | 8.0 | 16840 | 1.7726 | 0.8991 |
0.2771 | 9.0 | 18945 | 1.6832 | 0.8807 |
0.2565 | 10.0 | 21050 | 1.6899 | 0.8933 |
0.2434 | 11.0 | 23155 | 1.7471 | 0.8888 |
0.23 | 12.0 | 25260 | 2.1582 | 0.8704 |
0.2255 | 13.0 | 27365 | 1.8486 | 0.9037 |
0.2041 | 14.0 | 29470 | 1.6787 | 0.8922 |
0.218 | 15.0 | 31575 | 1.8426 | 0.8888 |
0.2027 | 16.0 | 33680 | 1.8820 | 0.8945 |
0.1924 | 17.0 | 35785 | 1.9447 | 0.8933 |
0.1964 | 18.0 | 37890 | 1.8394 | 0.8911 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for haryoaw/scenario-KD-SCR-DIV2-data-glue-sst2-model-bert-base-uncased-run-3
Base model
google-bert/bert-base-uncased