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---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: resnet-50-image-classification
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-50-image-classification
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3093
- Accuracy: 0.9408
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 101010
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log | 1.0 | 338 | 2.2768 | 0.5172 |
| 2.2806 | 2.0 | 676 | 2.0111 | 0.6903 |
| 1.8538 | 3.0 | 1014 | 1.2525 | 0.7467 |
| 1.8538 | 4.0 | 1352 | 0.6251 | 0.8578 |
| 0.8758 | 5.0 | 1690 | 0.3761 | 0.8967 |
| 0.4181 | 6.0 | 2028 | 0.2852 | 0.9144 |
| 0.4181 | 7.0 | 2366 | 0.2492 | 0.9244 |
| 0.2458 | 8.0 | 2704 | 0.2169 | 0.9364 |
| 0.1721 | 9.0 | 3042 | 0.2121 | 0.9358 |
| 0.1721 | 10.0 | 3380 | 0.2052 | 0.9403 |
| 0.1089 | 11.0 | 3718 | 0.2075 | 0.9414 |
| 0.0783 | 12.0 | 4056 | 0.2164 | 0.9367 |
| 0.0783 | 13.0 | 4394 | 0.2274 | 0.9381 |
| 0.0573 | 14.0 | 4732 | 0.2196 | 0.9433 |
| 0.0465 | 15.0 | 5070 | 0.2415 | 0.9381 |
| 0.0465 | 16.0 | 5408 | 0.2370 | 0.9433 |
| 0.0375 | 17.0 | 5746 | 0.2521 | 0.94 |
| 0.0288 | 18.0 | 6084 | 0.2533 | 0.9411 |
| 0.0288 | 19.0 | 6422 | 0.2608 | 0.9381 |
| 0.0253 | 20.0 | 6760 | 0.2602 | 0.9397 |
| 0.0207 | 21.0 | 7098 | 0.2712 | 0.94 |
| 0.0207 | 22.0 | 7436 | 0.2584 | 0.9408 |
| 0.0187 | 23.0 | 7774 | 0.2703 | 0.9419 |
| 0.012 | 24.0 | 8112 | 0.2772 | 0.9422 |
| 0.012 | 25.0 | 8450 | 0.2712 | 0.9419 |
| 0.0174 | 26.0 | 8788 | 0.2774 | 0.9422 |
| 0.0137 | 27.0 | 9126 | 0.2857 | 0.9414 |
| 0.0137 | 28.0 | 9464 | 0.2796 | 0.9428 |
| 0.0111 | 29.0 | 9802 | 0.3008 | 0.9367 |
| 0.0106 | 30.0 | 10140 | 0.2938 | 0.9369 |
| 0.0106 | 31.0 | 10478 | 0.2863 | 0.9406 |
| 0.0079 | 32.0 | 10816 | 0.2903 | 0.9425 |
| 0.0078 | 33.0 | 11154 | 0.2961 | 0.9419 |
| 0.0078 | 34.0 | 11492 | 0.2882 | 0.9417 |
| 0.0056 | 35.0 | 11830 | 0.2974 | 0.9406 |
| 0.0041 | 36.0 | 12168 | 0.2997 | 0.9419 |
| 0.0039 | 37.0 | 12506 | 0.3123 | 0.9367 |
| 0.0039 | 38.0 | 12844 | 0.3009 | 0.9408 |
| 0.0036 | 39.0 | 13182 | 0.3009 | 0.9422 |
| 0.0055 | 40.0 | 13520 | 0.3093 | 0.9408 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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