beit-large-patch16-384-limb-person-crop-8_1e-4_1e-3_0.15
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: 1.3620
- Accuracy: 0.3292
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: 0.0001
- 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: 0.15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.3978 | 1.0 | 214 | 1.3996 | 0.2761 |
1.3837 | 2.0 | 428 | 1.3840 | 0.2670 |
1.3936 | 3.0 | 642 | 1.3862 | 0.2745 |
1.3895 | 4.0 | 856 | 1.3875 | 0.2745 |
1.3866 | 5.0 | 1070 | 1.3853 | 0.2761 |
1.3916 | 6.0 | 1284 | 1.3840 | 0.2745 |
1.3808 | 7.0 | 1498 | 1.3804 | 0.3076 |
1.3712 | 8.0 | 1712 | 1.3740 | 0.3250 |
1.3737 | 9.0 | 1926 | 1.3683 | 0.3226 |
1.3553 | 10.0 | 2140 | 1.3620 | 0.3292 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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