metadata
base_model: uitnlp/visobert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: d-filter-v1.2
results: []
d-filter-v1.2
This model is a fine-tuned version of uitnlp/visobert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0881
- Accuracy: 0.9668
- F1: 0.8703
- Precision: 0.9044
- Recall: 0.8388
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1015 | 1.0 | 1414 | 0.0881 | 0.9668 | 0.8703 | 0.9044 | 0.8388 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.17.0
- Tokenizers 0.19.1