distilbert-base-uncased-finetuned-emrQA-msquad
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: 0.0218
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.2818 | 1.0 | 7836 | 0.2036 |
0.1229 | 2.0 | 15672 | 0.0739 |
0.0691 | 3.0 | 23508 | 0.0544 |
0.0478 | 4.0 | 31344 | 0.0321 |
0.0299 | 5.0 | 39180 | 0.0262 |
0.0178 | 6.0 | 47016 | 0.0261 |
0.0104 | 7.0 | 54852 | 0.0241 |
0.0058 | 8.0 | 62688 | 0.0218 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.13.1+cu116
- Datasets 2.19.2
- Tokenizers 0.19.1
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