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llm_science_bert
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6014
- Accuracy: 0.33
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: 0.003
- 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 25 | 1.6123 | 0.24 |
| No log | 2.0 | 50 | 1.6094 | 0.235 |
| 1.6308 | 3.0 | 75 | 1.6111 | 0.245 |
| 1.6308 | 4.0 | 100 | 1.6090 | 0.26 |
| 1.6308 | 5.0 | 125 | 1.6099 | 0.275 |
| 1.625 | 6.0 | 150 | 1.6088 | 0.28 |
| 1.625 | 7.0 | 175 | 1.6092 | 0.285 |
| 1.625 | 8.0 | 200 | 1.6070 | 0.28 |
| 1.616 | 9.0 | 225 | 1.6059 | 0.27 |
| 1.616 | 10.0 | 250 | 1.6049 | 0.285 |
| 1.616 | 11.0 | 275 | 1.6051 | 0.3 |
| 1.6134 | 12.0 | 300 | 1.6052 | 0.3 |
| 1.6134 | 13.0 | 325 | 1.6048 | 0.305 |
| 1.6134 | 14.0 | 350 | 1.6038 | 0.315 |
| 1.6179 | 15.0 | 375 | 1.6042 | 0.3 |
| 1.6179 | 16.0 | 400 | 1.6040 | 0.315 |
| 1.6179 | 17.0 | 425 | 1.6035 | 0.32 |
| 1.6113 | 18.0 | 450 | 1.6031 | 0.325 |
| 1.6113 | 19.0 | 475 | 1.6030 | 0.32 |
| 1.6113 | 20.0 | 500 | 1.6024 | 0.305 |
| 1.631 | 21.0 | 525 | 1.6024 | 0.31 |
| 1.631 | 22.0 | 550 | 1.6024 | 0.315 |
| 1.631 | 23.0 | 575 | 1.6023 | 0.32 |
| 1.6153 | 24.0 | 600 | 1.6021 | 0.315 |
| 1.6153 | 25.0 | 625 | 1.6020 | 0.325 |
| 1.6153 | 26.0 | 650 | 1.6018 | 0.33 |
| 1.6091 | 27.0 | 675 | 1.6017 | 0.33 |
| 1.6091 | 28.0 | 700 | 1.6016 | 0.33 |
| 1.6091 | 29.0 | 725 | 1.6015 | 0.33 |
| 1.6125 | 30.0 | 750 | 1.6014 | 0.33 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3
