metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_combined_top
results: []
bert_combined_top
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: 0.0320
- Accuracy: 0.9872
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9945 | 1.0 | 780 | 0.7471 | 0.7179 |
| 0.7659 | 2.0 | 1560 | 0.5219 | 0.8269 |
| 0.5512 | 3.0 | 2340 | 0.3141 | 0.9199 |
| 0.372 | 4.0 | 3120 | 0.2176 | 0.9519 |
| 0.2519 | 5.0 | 3900 | 0.1440 | 0.9679 |
| 0.172 | 6.0 | 4680 | 0.1142 | 0.9776 |
| 0.1873 | 7.0 | 5460 | 0.0943 | 0.9808 |
| 0.0807 | 8.0 | 6240 | 0.0449 | 0.9904 |
| 0.1075 | 9.0 | 7020 | 0.0432 | 0.9904 |
| 0.0479 | 10.0 | 7800 | 0.0320 | 0.9872 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0