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Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold1

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +14 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8600823045267489
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8616
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- - Accuracy: 0.8601
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.3225 | 1.0 | 914 | 0.3649 | 0.8442 |
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- | 0.3719 | 2.0 | 1828 | 0.3320 | 0.8700 |
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- | 0.2462 | 3.0 | 2742 | 0.4391 | 0.8565 |
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- | 0.086 | 4.0 | 3656 | 0.7110 | 0.8606 |
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- | 0.0239 | 5.0 | 4570 | 0.8616 | 0.8601 |
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8548696844993141
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5790
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+ - Accuracy: 0.8549
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.3103 | 1.0 | 914 | 0.3588 | 0.8494 |
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+ | 0.3671 | 2.0 | 1828 | 0.3382 | 0.8669 |
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+ | 0.2679 | 3.0 | 2742 | 0.4568 | 0.8491 |
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+ | 0.13 | 4.0 | 3656 | 0.7675 | 0.8595 |
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+ | 0.0539 | 5.0 | 4570 | 1.0063 | 0.8543 |
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+ | 0.0034 | 6.0 | 5484 | 1.3345 | 0.8543 |
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+ | 0.001 | 7.0 | 6398 | 1.4146 | 0.8562 |
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+ | 0.0013 | 8.0 | 7312 | 1.6343 | 0.8529 |
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+ | 0.0023 | 9.0 | 8226 | 1.5956 | 0.8486 |
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+ | 0.0001 | 10.0 | 9140 | 1.5790 | 0.8549 |
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  ### Framework versions
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