metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: NHS-distilbert-binary-random
results: []
NHS-distilbert-binary-random
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5121
- Accuracy: 0.8019
- Precision: 0.7972
- Recall: 0.8065
- F1: 0.7988
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 |
|---|---|---|---|---|---|---|---|
| 0.1385 | 1.0 | 397 | 0.4277 | 0.8069 | 0.8004 | 0.7989 | 0.7996 |
| 0.0481 | 2.0 | 794 | 0.4580 | 0.7931 | 0.7894 | 0.7990 | 0.7903 |
| 2.0213 | 3.0 | 1191 | 0.5121 | 0.8019 | 0.7972 | 0.8065 | 0.7988 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2