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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: Action_agent |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8019047619047619 |
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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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# Action_agent |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6758 |
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- Accuracy: 0.8019 |
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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: 1e-05 |
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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: 20 |
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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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| 2.1987 | 0.32 | 100 | 2.1640 | 0.3914 | |
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| 1.9807 | 0.64 | 200 | 1.9169 | 0.6143 | |
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| 1.6738 | 0.96 | 300 | 1.6148 | 0.72 | |
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| 1.4828 | 1.27 | 400 | 1.3861 | 0.7705 | |
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| 1.2768 | 1.59 | 500 | 1.2412 | 0.7590 | |
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| 1.1759 | 1.91 | 600 | 1.1169 | 0.7914 | |
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| 1.0314 | 2.23 | 700 | 1.0599 | 0.7762 | |
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| 0.9702 | 2.55 | 800 | 0.9640 | 0.8105 | |
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| 0.9559 | 2.87 | 900 | 0.9138 | 0.8076 | |
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| 0.858 | 3.18 | 1000 | 0.8605 | 0.8248 | |
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| 0.7858 | 3.5 | 1100 | 0.8164 | 0.8371 | |
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| 0.7898 | 3.82 | 1200 | 0.7917 | 0.8333 | |
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| 0.6909 | 4.14 | 1300 | 0.7995 | 0.8038 | |
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| 0.6619 | 4.46 | 1400 | 0.8194 | 0.7829 | |
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| 0.6457 | 4.78 | 1500 | 0.7536 | 0.8086 | |
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| 0.6155 | 5.1 | 1600 | 0.7212 | 0.8257 | |
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| 0.5511 | 5.41 | 1700 | 0.7274 | 0.8095 | |
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| 0.5486 | 5.73 | 1800 | 0.7048 | 0.8286 | |
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| 0.5679 | 6.05 | 1900 | 0.7124 | 0.8181 | |
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| 0.4914 | 6.37 | 2000 | 0.7277 | 0.8010 | |
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| 0.525 | 6.69 | 2100 | 0.6971 | 0.8124 | |
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| 0.5081 | 7.01 | 2200 | 0.6869 | 0.8162 | |
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| 0.5072 | 7.32 | 2300 | 0.6837 | 0.8076 | |
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| 0.4702 | 7.64 | 2400 | 0.6736 | 0.8152 | |
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| 0.4303 | 7.96 | 2500 | 0.6693 | 0.8105 | |
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| 0.3916 | 8.28 | 2600 | 0.6487 | 0.8238 | |
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| 0.4002 | 8.6 | 2700 | 0.6661 | 0.8162 | |
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| 0.3965 | 8.92 | 2800 | 0.6611 | 0.8143 | |
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| 0.3946 | 9.24 | 2900 | 0.6523 | 0.8143 | |
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| 0.3794 | 9.55 | 3000 | 0.6616 | 0.8048 | |
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| 0.3257 | 9.87 | 3100 | 0.6717 | 0.8029 | |
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| 0.4175 | 10.19 | 3200 | 0.6530 | 0.8057 | |
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| 0.3559 | 10.51 | 3300 | 0.6883 | 0.7886 | |
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| 0.3824 | 10.83 | 3400 | 0.6611 | 0.8 | |
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| 0.3589 | 11.15 | 3500 | 0.6659 | 0.8019 | |
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| 0.3299 | 11.46 | 3600 | 0.6819 | 0.7962 | |
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| 0.3736 | 11.78 | 3700 | 0.6405 | 0.8114 | |
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| 0.3576 | 12.1 | 3800 | 0.6725 | 0.7962 | |
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| 0.3454 | 12.42 | 3900 | 0.7025 | 0.7943 | |
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| 0.3049 | 12.74 | 4000 | 0.6439 | 0.8133 | |
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| 0.3363 | 13.06 | 4100 | 0.6352 | 0.8143 | |
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| 0.3273 | 13.38 | 4200 | 0.6795 | 0.7886 | |
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| 0.283 | 13.69 | 4300 | 0.6705 | 0.8 | |
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| 0.2607 | 14.01 | 4400 | 0.6732 | 0.7914 | |
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| 0.3174 | 14.33 | 4500 | 0.6691 | 0.8048 | |
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| 0.3189 | 14.65 | 4600 | 0.6602 | 0.8038 | |
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| 0.2862 | 14.97 | 4700 | 0.6801 | 0.7933 | |
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| 0.2895 | 15.29 | 4800 | 0.6579 | 0.8038 | |
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| 0.263 | 15.61 | 4900 | 0.6688 | 0.8 | |
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| 0.3214 | 15.92 | 5000 | 0.6547 | 0.8057 | |
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| 0.2867 | 16.24 | 5100 | 0.6775 | 0.7924 | |
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| 0.2242 | 16.56 | 5200 | 0.6378 | 0.8086 | |
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| 0.2839 | 16.88 | 5300 | 0.6761 | 0.7990 | |
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| 0.2424 | 17.2 | 5400 | 0.6386 | 0.8124 | |
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| 0.2666 | 17.52 | 5500 | 0.6493 | 0.8133 | |
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| 0.2259 | 17.83 | 5600 | 0.6514 | 0.8048 | |
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| 0.2533 | 18.15 | 5700 | 0.6676 | 0.8 | |
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| 0.2697 | 18.47 | 5800 | 0.6705 | 0.8010 | |
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| 0.2558 | 18.79 | 5900 | 0.6750 | 0.8076 | |
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| 0.2469 | 19.11 | 6000 | 0.6751 | 0.7990 | |
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| 0.284 | 19.43 | 6100 | 0.6738 | 0.7981 | |
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| 0.2534 | 19.75 | 6200 | 0.6758 | 0.8019 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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