metadata
license: apache-2.0
base_model: dandelin/vilt-b32-mlm
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: vilt_finetuned_2
results: []
vilt_finetuned_2
This model is a fine-tuned version of dandelin/vilt-b32-mlm on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3663
- F1: 0.6000
- Roc Auc: 0.7866
- Accuracy: 0.5735
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 44.1455 | 1.0 | 129 | 6.5479 | 0.1270 | 0.5367 | 0.0735 |
| 2.9608 | 2.0 | 258 | 2.7634 | 0.4385 | 0.6965 | 0.3934 |
| 2.3046 | 3.0 | 387 | 2.4919 | 0.4948 | 0.7204 | 0.4412 |
| 1.895 | 4.0 | 516 | 2.3418 | 0.5652 | 0.7627 | 0.5257 |
| 1.4785 | 5.0 | 645 | 2.6462 | 0.5720 | 0.7701 | 0.5404 |
| 1.1491 | 6.0 | 774 | 2.8805 | 0.6074 | 0.7884 | 0.5772 |
| 0.8297 | 7.0 | 903 | 3.1832 | 0.5977 | 0.7866 | 0.5735 |
| 0.7249 | 8.0 | 1032 | 3.2679 | 0.6054 | 0.7903 | 0.5809 |
| 2.1554 | 9.0 | 1161 | 3.2926 | 0.6119 | 0.7940 | 0.5846 |
| 0.5323 | 10.0 | 1290 | 3.3663 | 0.6000 | 0.7866 | 0.5735 |
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2