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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: exper_batch_32_e4
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results: []
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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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should probably proofread and complete it, then remove this comment. -->
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# exper_batch_32_e4
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3909
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- Accuracy: 0.9067
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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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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- num_epochs: 4
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- mixed_precision_training: Apex, opt level O1
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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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| 3.4295 | 0.31 | 100 | 3.4027 | 0.2837 |
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| 2.5035 | 0.62 | 200 | 2.4339 | 0.5247 |
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| 1.6542 | 0.94 | 300 | 1.7690 | 0.6388 |
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| 1.1589 | 1.25 | 400 | 1.3106 | 0.7460 |
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| 0.9363 | 1.56 | 500 | 0.9977 | 0.7803 |
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| 0.6946 | 1.88 | 600 | 0.8138 | 0.8207 |
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| 0.3488 | 2.19 | 700 | 0.6593 | 0.8489 |
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| 0.2935 | 2.5 | 800 | 0.5725 | 0.8662 |
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| 0.2557 | 2.81 | 900 | 0.5088 | 0.8855 |
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| 0.1509 | 3.12 | 1000 | 0.4572 | 0.8971 |
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| 0.1367 | 3.44 | 1100 | 0.4129 | 0.9090 |
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| 0.1078 | 3.75 | 1200 | 0.3909 | 0.9067 |
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### Framework versions
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- Transformers 4.19.4
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- Pytorch 1.5.1
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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