metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_bert-base-uncased
results: []
finetuned_bert-base-uncased
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: 1.0293
- Accuracy: 0.6664
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: 2e-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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 204 | 1.0807 | 0.6586 |
| No log | 2.0 | 408 | 1.2250 | 0.6760 |
| 0.271 | 3.0 | 612 | 1.1975 | 0.6663 |
| 0.271 | 4.0 | 816 | 1.2170 | 0.6625 |
| 0.2395 | 5.0 | 1020 | 1.2817 | 0.6702 |
| 0.2395 | 6.0 | 1224 | 1.4138 | 0.6634 |
| 0.2395 | 7.0 | 1428 | 1.5268 | 0.6819 |
| 0.1661 | 8.0 | 1632 | 1.5753 | 0.6702 |
| 0.1661 | 9.0 | 1836 | 1.6794 | 0.6663 |
| 0.1349 | 10.0 | 2040 | 1.6416 | 0.6731 |
| 0.1349 | 11.0 | 2244 | 1.7056 | 0.6741 |
| 0.1349 | 12.0 | 2448 | 1.7374 | 0.6760 |
| 0.1159 | 13.0 | 2652 | 1.8817 | 0.6644 |
| 0.1159 | 14.0 | 2856 | 1.7318 | 0.6751 |
| 0.111 | 15.0 | 3060 | 1.8213 | 0.6712 |
| 0.111 | 16.0 | 3264 | 1.8347 | 0.6722 |
| 0.111 | 17.0 | 3468 | 1.8072 | 0.6780 |
| 0.0988 | 18.0 | 3672 | 1.8371 | 0.6770 |
| 0.0988 | 19.0 | 3876 | 1.8562 | 0.6741 |
| 0.0907 | 20.0 | 4080 | 1.8583 | 0.6741 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2