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hushem_1x_deit_tiny_adamax_lr0001_fold1

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  2. model.safetensors +1 -1
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-tiny-patch16-224
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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: hushem_1x_deit_tiny_adamax_lr0001_fold1
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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: test
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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: 0.5777777777777777
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+ ---
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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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+
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+ # hushem_1x_deit_tiny_adamax_lr0001_fold1
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3365
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+ - Accuracy: 0.5778
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.67 | 1 | 1.6054 | 0.2444 |
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+ | No log | 2.0 | 3 | 1.3436 | 0.3556 |
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+ | No log | 2.67 | 4 | 1.3392 | 0.2889 |
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+ | No log | 4.0 | 6 | 1.3661 | 0.2444 |
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+ | No log | 4.67 | 7 | 1.3117 | 0.3333 |
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+ | No log | 6.0 | 9 | 1.4031 | 0.2889 |
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+ | 1.1803 | 6.67 | 10 | 1.2845 | 0.4222 |
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+ | 1.1803 | 8.0 | 12 | 1.3559 | 0.3333 |
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+ | 1.1803 | 8.67 | 13 | 1.3178 | 0.4 |
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+ | 1.1803 | 10.0 | 15 | 1.1302 | 0.5778 |
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+ | 1.1803 | 10.67 | 16 | 1.2145 | 0.5556 |
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+ | 1.1803 | 12.0 | 18 | 1.3484 | 0.4 |
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+ | 1.1803 | 12.67 | 19 | 1.1709 | 0.5333 |
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+ | 0.3935 | 14.0 | 21 | 1.1495 | 0.5556 |
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+ | 0.3935 | 14.67 | 22 | 1.2656 | 0.4889 |
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+ | 0.3935 | 16.0 | 24 | 1.1929 | 0.5333 |
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+ | 0.3935 | 16.67 | 25 | 1.1205 | 0.5556 |
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+ | 0.3935 | 18.0 | 27 | 1.1729 | 0.5333 |
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+ | 0.3935 | 18.67 | 28 | 1.2656 | 0.5111 |
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+ | 0.0911 | 20.0 | 30 | 1.3172 | 0.5556 |
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+ | 0.0911 | 20.67 | 31 | 1.2343 | 0.5556 |
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+ | 0.0911 | 22.0 | 33 | 1.1439 | 0.6 |
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+ | 0.0911 | 22.67 | 34 | 1.1167 | 0.6222 |
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+ | 0.0911 | 24.0 | 36 | 1.1537 | 0.6 |
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+ | 0.0911 | 24.67 | 37 | 1.2658 | 0.5778 |
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+ | 0.0911 | 26.0 | 39 | 1.3705 | 0.5556 |
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+ | 0.0269 | 26.67 | 40 | 1.3468 | 0.5778 |
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+ | 0.0269 | 28.0 | 42 | 1.2914 | 0.6 |
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+ | 0.0269 | 28.67 | 43 | 1.2807 | 0.6 |
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+ | 0.0269 | 30.0 | 45 | 1.2833 | 0.6 |
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+ | 0.0269 | 30.67 | 46 | 1.3004 | 0.5778 |
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+ | 0.0269 | 32.0 | 48 | 1.3271 | 0.5778 |
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+ | 0.0269 | 32.67 | 49 | 1.3342 | 0.5778 |
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+ | 0.0102 | 33.33 | 50 | 1.3365 | 0.5778 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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