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cvt-13-finetuned-IDRiD

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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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+ 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: cvt-13-finetuned-IDRiD
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+ results: []
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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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+ # cvt-13-finetuned-IDRiD
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+
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+ This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2520
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+ - Accuracy: 0.4524
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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: 30
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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 | 1.0 | 3 | 1.6800 | 0.1190 |
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+ | No log | 2.0 | 6 | 1.6686 | 0.2143 |
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+ | No log | 3.0 | 9 | 1.5528 | 0.3333 |
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+ | 1.6061 | 4.0 | 12 | 1.4874 | 0.3333 |
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+ | 1.6061 | 5.0 | 15 | 1.4834 | 0.3571 |
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+ | 1.6061 | 6.0 | 18 | 1.4485 | 0.3810 |
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+ | 1.4325 | 7.0 | 21 | 1.4295 | 0.4048 |
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+ | 1.4325 | 8.0 | 24 | 1.4172 | 0.4286 |
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+ | 1.4325 | 9.0 | 27 | 1.3890 | 0.4048 |
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+ | 1.3474 | 10.0 | 30 | 1.3739 | 0.4286 |
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+ | 1.3474 | 11.0 | 33 | 1.3571 | 0.4048 |
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+ | 1.3474 | 12.0 | 36 | 1.3244 | 0.4048 |
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+ | 1.3474 | 13.0 | 39 | 1.3090 | 0.4048 |
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+ | 1.3039 | 14.0 | 42 | 1.3438 | 0.4286 |
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+ | 1.3039 | 15.0 | 45 | 1.3617 | 0.4286 |
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+ | 1.3039 | 16.0 | 48 | 1.3513 | 0.4286 |
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+ | 1.2892 | 17.0 | 51 | 1.3187 | 0.4524 |
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+ | 1.2892 | 18.0 | 54 | 1.3054 | 0.3810 |
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+ | 1.2892 | 19.0 | 57 | 1.2862 | 0.4286 |
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+ | 1.2489 | 20.0 | 60 | 1.2670 | 0.4524 |
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+ | 1.2489 | 21.0 | 63 | 1.2810 | 0.4762 |
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+ | 1.2489 | 22.0 | 66 | 1.2389 | 0.4524 |
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+ | 1.2489 | 23.0 | 69 | 1.2312 | 0.4762 |
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+ | 1.2378 | 24.0 | 72 | 1.2619 | 0.4524 |
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+ | 1.2378 | 25.0 | 75 | 1.2652 | 0.4524 |
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+ | 1.2378 | 26.0 | 78 | 1.2639 | 0.4524 |
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+ | 1.1968 | 27.0 | 81 | 1.2517 | 0.4524 |
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+ | 1.1968 | 28.0 | 84 | 1.2603 | 0.4286 |
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+ | 1.1968 | 29.0 | 87 | 1.2463 | 0.4524 |
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+ | 1.1977 | 30.0 | 90 | 1.2520 | 0.4524 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.13.3