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update model card README.md

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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/resnet-50
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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: resnet-50-finetuned-masked-hateful-meme-restructured
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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: validation
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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: 0.5
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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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+ # resnet-50-finetuned-masked-hateful-meme-restructured
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+
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+ This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7093
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+ - Accuracy: 0.5
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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: 5e-05
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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: 10
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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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+ | 0.6639 | 0.99 | 66 | 0.7093 | 0.5 |
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+ | 0.6569 | 2.0 | 133 | 0.7295 | 0.5 |
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+ | 0.6489 | 2.99 | 199 | 0.7257 | 0.5 |
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+ | 0.6553 | 4.0 | 266 | 0.7274 | 0.5 |
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+ | 0.6334 | 4.99 | 332 | 0.7311 | 0.5 |
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+ | 0.627 | 6.0 | 399 | 0.7371 | 0.5 |
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+ | 0.6561 | 6.99 | 465 | 0.7386 | 0.5 |
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+ | 0.6552 | 8.0 | 532 | 0.7354 | 0.5 |
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+ | 0.6427 | 8.99 | 598 | 0.7346 | 0.5 |
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+ | 0.6451 | 9.92 | 660 | 0.7377 | 0.498 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3