beit-large-patch16-384-limb-person-crop-8_5e-5_1e-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: 0.7900
- Accuracy: 0.7786
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: 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 |
---|---|---|---|---|
1.328 | 1.0 | 214 | 1.5084 | 0.3682 |
1.1745 | 2.0 | 428 | 1.0144 | 0.6269 |
1.1391 | 3.0 | 642 | 0.9256 | 0.6774 |
1.0591 | 4.0 | 856 | 0.9510 | 0.6534 |
1.0509 | 5.0 | 1070 | 0.8972 | 0.6949 |
0.9764 | 6.0 | 1284 | 0.8174 | 0.7521 |
0.9019 | 7.0 | 1498 | 0.8268 | 0.7421 |
0.8834 | 8.0 | 1712 | 0.7919 | 0.7662 |
0.81 | 9.0 | 1926 | 0.8003 | 0.7736 |
0.8065 | 10.0 | 2140 | 0.7900 | 0.7786 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 0