distilbert-clinical-ner
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: 0.3672
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 36 | 0.2829 |
No log | 2.0 | 72 | 0.2953 |
No log | 3.0 | 108 | 0.3107 |
No log | 4.0 | 144 | 0.3310 |
No log | 5.0 | 180 | 0.3451 |
No log | 6.0 | 216 | 0.3449 |
No log | 7.0 | 252 | 0.3620 |
No log | 8.0 | 288 | 0.3668 |
No log | 9.0 | 324 | 0.3661 |
No log | 10.0 | 360 | 0.3672 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Tokenizers 0.19.1
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Model tree for ribhu/distilbert-clinical-ner
Base model
distilbert/distilbert-base-uncased