transformers safetensors resnet image-classification generated_from_trainer base_model:microsoft/resnet-50 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
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
