metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: yelp_normal
results: []
yelp_normal
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: 1.6616
- Accuracy: 0.61
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: 5e-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 |
---|---|---|---|---|
1.1329 | 1.0 | 375 | 0.9700 | 0.5835 |
0.799 | 2.0 | 750 | 0.9890 | 0.597 |
0.5304 | 3.0 | 1125 | 1.1025 | 0.614 |
0.2933 | 4.0 | 1500 | 1.4188 | 0.6035 |
0.1342 | 5.0 | 1875 | 1.6616 | 0.61 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2