metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trained_model_distilbert_0305
results: []
trained_model_distilbert_0305
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: 0.5584
- Accuracy: 0.8158
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 57 | 0.8234 | 0.6930 |
| No log | 2.0 | 114 | 0.7279 | 0.6930 |
| No log | 3.0 | 171 | 0.5902 | 0.7675 |
| No log | 4.0 | 228 | 0.5336 | 0.7632 |
| No log | 5.0 | 285 | 0.5117 | 0.7851 |
| No log | 6.0 | 342 | 0.5355 | 0.7807 |
| No log | 7.0 | 399 | 0.5005 | 0.8333 |
| No log | 8.0 | 456 | 0.5282 | 0.8289 |
| 0.4628 | 9.0 | 513 | 0.5481 | 0.8333 |
| 0.4628 | 10.0 | 570 | 0.5584 | 0.8158 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1