metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: newly_fine_tuned_bert
results: []
newly_fine_tuned_bert
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: 0.0706
- F1: 0.0
- Roc Auc: 0.5
- Accuracy: 0.0
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.2056 | 1.0 | 22 | 0.1966 | 0.0385 | 0.4756 | 0.0 |
| 0.175 | 2.0 | 44 | 0.1566 | 0.0488 | 0.5140 | 0.0 |
| 0.1397 | 3.0 | 66 | 0.1229 | 0.0 | 0.4988 | 0.0 |
| 0.1154 | 4.0 | 88 | 0.1032 | 0.0 | 0.5 | 0.0 |
| 0.093 | 5.0 | 110 | 0.0894 | 0.0 | 0.5 | 0.0 |
| 0.0827 | 6.0 | 132 | 0.0788 | 0.0 | 0.5 | 0.0 |
| 0.0737 | 7.0 | 154 | 0.0706 | 0.0 | 0.5 | 0.0 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1