metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-base-web3-project-categories
results: []
roberta-base-web3-project-categories
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1910
- Accuracy: 0.6560
- F1: 0.6383
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: 32
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.3519 | 1.0 | 2722 | 1.3109 | 0.5791 | 0.5253 |
| 1.1631 | 2.0 | 5444 | 1.2101 | 0.6065 | 0.5830 |
| 0.9798 | 3.0 | 8166 | 1.1707 | 0.6330 | 0.6083 |
| 0.8552 | 4.0 | 10888 | 1.1671 | 0.6441 | 0.6238 |
| 0.6935 | 5.0 | 13610 | 1.1910 | 0.6560 | 0.6383 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1