MC_proteome_literature_classification_balanced
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9679
- Accuracy: 0.4494
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: 1
- eval_batch_size: 1
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 263 | 2.0873 | 0.3483 |
| 1.9438 | 2.0 | 526 | 1.9461 | 0.4157 |
| 1.9438 | 3.0 | 789 | 1.9642 | 0.4382 |
| 1.5822 | 4.0 | 1052 | 3.0854 | 0.4270 |
| 1.5822 | 5.0 | 1315 | 2.9679 | 0.4494 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for seven-wind-c/MC_proteome_literature_classification_balanced
Base model
distilbert/distilbert-base-uncased