beit-large-patch16-384-limb-person-crop-8_1e-5_5e-3_0.1
This model is a fine-tuned version of microsoft/beit-large-patch16-384 on the c14kevincardenas/beta_caller_284_person_crop dataset. It achieves the following results on the evaluation set:
- Loss: 0.8764
- Accuracy: 0.7181
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2014
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.4023 | 1.0 | 214 | 1.3975 | 0.2745 |
1.2554 | 2.0 | 428 | 1.1980 | 0.4900 |
1.1635 | 3.0 | 642 | 1.0272 | 0.5970 |
1.099 | 4.0 | 856 | 1.0476 | 0.5954 |
1.067 | 5.0 | 1070 | 0.9586 | 0.6600 |
1.0153 | 6.0 | 1284 | 0.9101 | 0.6816 |
0.9507 | 7.0 | 1498 | 0.9307 | 0.6833 |
0.9487 | 8.0 | 1712 | 0.8812 | 0.7148 |
0.9365 | 9.0 | 1926 | 0.8764 | 0.7181 |
0.9186 | 10.0 | 2140 | 0.8818 | 0.7090 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 0