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: 0.9064
- Accuracy: 0.6591
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 204 | 0.9670 | 0.6052 |
| No log | 2.0 | 408 | 0.8899 | 0.6731 |
| 0.8476 | 3.0 | 612 | 0.9283 | 0.6722 |
| 0.8476 | 4.0 | 816 | 1.0110 | 0.6828 |
| 0.3419 | 5.0 | 1020 | 1.0947 | 0.6741 |
| 0.3419 | 6.0 | 1224 | 1.1896 | 0.6799 |
| 0.3419 | 7.0 | 1428 | 1.3467 | 0.6887 |
| 0.193 | 8.0 | 1632 | 1.3716 | 0.6838 |
| 0.193 | 9.0 | 1836 | 1.4742 | 0.6809 |
| 0.1485 | 10.0 | 2040 | 1.5121 | 0.6867 |
| 0.1485 | 11.0 | 2244 | 1.5670 | 0.6819 |
| 0.1485 | 12.0 | 2448 | 1.5593 | 0.6867 |
| 0.1185 | 13.0 | 2652 | 1.6455 | 0.6809 |
| 0.1185 | 14.0 | 2856 | 1.6417 | 0.6877 |
| 0.1077 | 15.0 | 3060 | 1.6399 | 0.6867 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2