metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: zooguide_bert_checkpoints
results: []
zooguide_bert_checkpoints
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0865
- Accuracy: 0.9667
- Macro F1: 0.9663
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| 1.2682 | 1.0 | 132 | 0.2280 | 0.9689 | 0.9691 |
| 0.1257 | 2.0 | 264 | 0.1087 | 0.9689 | 0.9692 |
| 0.0717 | 3.0 | 396 | 0.0695 | 0.98 | 0.9798 |
| 0.0612 | 4.0 | 528 | 0.0621 | 0.9711 | 0.9711 |
| 0.0493 | 5.0 | 660 | 0.0580 | 0.9689 | 0.9691 |
| 0.0436 | 6.0 | 792 | 0.0607 | 0.9667 | 0.9669 |
| 0.0403 | 7.0 | 924 | 0.0628 | 0.96 | 0.9603 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2