Heritage-in-the-Digital-Age-finetuned
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6727
- Accuracy: 0.5845
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: 2e-05
- train_batch_size: 15
- eval_batch_size: 15
- 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 | 22 | 0.6727 | 0.5845 |
No log | 2.0 | 44 | 0.6727 | 0.5845 |
No log | 3.0 | 66 | 0.6727 | 0.5845 |
No log | 4.0 | 88 | 0.6727 | 0.5845 |
No log | 5.0 | 110 | 0.6727 | 0.5845 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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