metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-web3-classification
results: []
distilbert-web3-classification
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: 1.2908
- Accuracy: 0.6672
- F1: 0.6550
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: 32
- eval_batch_size: 64
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.4162 | 1.0 | 1361 | 1.3294 | 0.5749 | 0.5271 |
| 1.1807 | 2.0 | 2722 | 1.2292 | 0.6163 | 0.5789 |
| 0.9574 | 3.0 | 4083 | 1.1857 | 0.6430 | 0.6207 |
| 0.7361 | 4.0 | 5444 | 1.1896 | 0.6688 | 0.6510 |
| 0.5548 | 5.0 | 6805 | 1.2908 | 0.6672 | 0.6550 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1