metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-set_3
results: []
bert-base-uncased-finetuned-set_3
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: 2.1865
- Accuracy: 0.7300
- Qwk: 0.6937
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Qwk |
|---|---|---|---|---|---|
| No log | 1.0 | 91 | 2.3480 | 0.7245 | 0.6519 |
| No log | 2.0 | 182 | 2.1615 | 0.7273 | 0.6827 |
| No log | 3.0 | 273 | 2.2337 | 0.7107 | 0.6739 |
| No log | 4.0 | 364 | 2.1598 | 0.7218 | 0.7019 |
| No log | 5.0 | 455 | 2.1865 | 0.7300 | 0.6937 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1