metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 0.50-800Train-100Test-beit-base
results: []
0.50-800Train-100Test-beit-base
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7501
- Accuracy: 0.8192
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: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7627 | 0.9536 | 18 | 0.6991 | 0.7860 |
| 0.3414 | 1.9603 | 37 | 0.5881 | 0.8070 |
| 0.1402 | 2.9669 | 56 | 0.5879 | 0.8114 |
| 0.0663 | 3.9735 | 75 | 0.6249 | 0.8175 |
| 0.0377 | 4.9801 | 94 | 0.6539 | 0.8210 |
| 0.0314 | 5.9868 | 113 | 0.7074 | 0.8175 |
| 0.0189 | 6.9934 | 132 | 0.7596 | 0.8210 |
| 0.0147 | 8.0 | 151 | 0.7211 | 0.8253 |
| 0.0157 | 8.9536 | 169 | 0.7412 | 0.8166 |
| 0.0095 | 9.5364 | 180 | 0.7501 | 0.8192 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1