metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: NHS-bert-multi
results: []
NHS-bert-multi
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9010
- Accuracy: 0.7085
- Precision: 0.7137
- Recall: 0.7085
- F1: 0.7084
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2418 | 1.0 | 397 | 0.7491 | 0.7009 | 0.7118 | 0.7009 | 0.7040 |
| 0.0444 | 2.0 | 794 | 0.7778 | 0.7129 | 0.7106 | 0.7129 | 0.7040 |
| 1.1342 | 3.0 | 1191 | 0.9010 | 0.7085 | 0.7137 | 0.7085 | 0.7084 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2