transformers tensorboard 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
  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

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0320
- Accuracy: 0.5186

## 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: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3301        | 1.0   | 32   | 1.3377          | 0.3477   |
| 1.2001        | 2.0   | 64   | 1.2172          | 0.4414   |
| 1.1188        | 3.0   | 96   | 1.1265          | 0.5010   |
| 1.0655        | 4.0   | 128  | 1.1025          | 0.5010   |
| 1.0437        | 5.0   | 160  | 1.0753          | 0.5010   |
| 1.0374        | 6.0   | 192  | 1.0629          | 0.5029   |
| 1.0181        | 7.0   | 224  | 1.0452          | 0.5137   |
| 1.0011        | 8.0   | 256  | 1.0381          | 0.5127   |
| 1.0074        | 9.0   | 288  | 1.0268          | 0.5098   |
| 0.9977        | 10.0  | 320  | 1.0320          | 0.5186   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
