bert-base-uncased
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 60 | nan |
| 0.3696 | 2.0 | 120 | nan |
| 0.3696 | 3.0 | 180 | nan |
| 0.1117 | 4.0 | 240 | nan |
| 0.0942 | 5.0 | 300 | nan |
| 0.0942 | 6.0 | 360 | nan |
| 0.0894 | 7.0 | 420 | nan |
| 0.0894 | 8.0 | 480 | nan |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Downloads last month
- 6
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for rseeto/multilabel_disease_bert_classification
Base model
google-bert/bert-base-uncased