workornot
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: 0.3372
- Accuracy: 0.856
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 125 | 0.6385 | 0.787 |
| No log | 2.0 | 250 | 0.5578 | 0.808 |
| No log | 3.0 | 375 | 0.4489 | 0.818 |
| 0.5423 | 4.0 | 500 | 0.3610 | 0.843 |
| 0.5423 | 5.0 | 625 | 0.3374 | 0.855 |
| 0.5423 | 6.0 | 750 | 0.3365 | 0.854 |
| 0.5423 | 7.0 | 875 | 0.3331 | 0.857 |
| 0.3101 | 8.0 | 1000 | 0.3359 | 0.857 |
| 0.3101 | 9.0 | 1125 | 0.3377 | 0.855 |
| 0.3101 | 10.0 | 1250 | 0.3372 | 0.856 |
Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for MaggieZhang/workornot
Base model
distilbert/distilbert-base-uncased