distilbert-base-uncased-finetuned-wikiandmark
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: 0.0329
- Accuracy: 0.9962
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: 32
- eval_batch_size: 32
- 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 |
---|---|---|---|---|
0.0058 | 1.0 | 1490 | 0.0261 | 0.9954 |
0.0058 | 2.0 | 2980 | 0.0335 | 0.9945 |
0.0024 | 3.0 | 4470 | 0.0309 | 0.9961 |
0.0007 | 4.0 | 5960 | 0.0323 | 0.9961 |
0.0009 | 5.0 | 7450 | 0.0329 | 0.9962 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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