distilbert-base-uncased-finetuned-mathqa
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5056
- Accuracy: 0.3445
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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5584 | 1.0 | 2970 | 1.5429 | 0.3029 |
| 1.485 | 2.0 | 5940 | 1.4965 | 0.3328 |
| 1.3677 | 3.0 | 8910 | 1.5056 | 0.3445 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for nickrwu/distilbert-base-uncased-finetuned-mathqa
Base model
distilbert/distilbert-base-uncased