metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: mvit_v2_rwf-2000
results: []
mvit_v2_rwf-2000
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3786
- Accuracy: 0.8875
- F1: 0.8873
- Precision: 0.8907
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1520
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
|---|---|---|---|---|---|---|
| 0.4242 | 0.125 | 190 | 0.4227 | 0.8375 | 0.8366 | 0.8453 |
| 0.3906 | 1.125 | 380 | 0.2933 | 0.9 | 0.8999 | 0.9010 |
| 0.3199 | 2.125 | 570 | 0.3034 | 0.9313 | 0.9312 | 0.9313 |
| 0.2239 | 3.125 | 760 | 0.3611 | 0.9125 | 0.9124 | 0.9135 |
| 0.1747 | 4.125 | 950 | 0.3475 | 0.9313 | 0.9312 | 0.9313 |
| 0.1702 | 5.125 | 1140 | 0.3667 | 0.9313 | 0.9312 | 0.9313 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.0.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1