transformers safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ProteinClassificationModelV2
  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. -->

# ProteinClassificationModelV2

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4631
- Accuracy: 0.92

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.707         | 1.0   | 113  | 0.3861          | 0.845    |
| 0.3382        | 2.0   | 226  | 0.3137          | 0.87     |
| 0.2635        | 3.0   | 339  | 0.2881          | 0.885    |
| 0.2469        | 4.0   | 452  | 0.3090          | 0.88     |
| 0.1995        | 5.0   | 565  | 0.2577          | 0.92     |
| 0.1869        | 6.0   | 678  | 0.2783          | 0.91     |
| 0.1799        | 7.0   | 791  | 0.2146          | 0.925    |
| 0.1376        | 8.0   | 904  | 0.3013          | 0.89     |
| 0.1079        | 9.0   | 1017 | 0.4004          | 0.885    |
| 0.1207        | 10.0  | 1130 | 0.5334          | 0.85     |
| 0.089         | 11.0  | 1243 | 0.3145          | 0.93     |
| 0.1056        | 12.0  | 1356 | 0.3250          | 0.9      |
| 0.1087        | 13.0  | 1469 | 0.4588          | 0.89     |
| 0.0746        | 14.0  | 1582 | 0.3866          | 0.895    |
| 0.081         | 15.0  | 1695 | 0.3356          | 0.905    |
| 0.0539        | 16.0  | 1808 | 0.5468          | 0.89     |
| 0.0772        | 17.0  | 1921 | 0.4060          | 0.895    |
| 0.0729        | 18.0  | 2034 | 0.5682          | 0.875    |
| 0.0525        | 19.0  | 2147 | 0.4364          | 0.905    |
| 0.0654        | 20.0  | 2260 | 0.3860          | 0.895    |
| 0.0461        | 21.0  | 2373 | 0.5711          | 0.895    |
| 0.0539        | 22.0  | 2486 | 0.6325          | 0.89     |
| 0.0309        | 23.0  | 2599 | 0.5805          | 0.885    |
| 0.0452        | 24.0  | 2712 | 0.4380          | 0.905    |
| 0.0406        | 25.0  | 2825 | 0.4316          | 0.9      |
| 0.0404        | 26.0  | 2938 | 0.4540          | 0.905    |
| 0.0288        | 27.0  | 3051 | 0.5276          | 0.915    |
| 0.0493        | 28.0  | 3164 | 0.6025          | 0.895    |
| 0.0244        | 29.0  | 3277 | 0.6028          | 0.9      |
| 0.025         | 30.0  | 3390 | 0.5895          | 0.915    |
| 0.0277        | 31.0  | 3503 | 0.4587          | 0.915    |
| 0.0284        | 32.0  | 3616 | 0.4466          | 0.915    |
| 0.029         | 33.0  | 3729 | 0.4343          | 0.905    |
| 0.021         | 34.0  | 3842 | 0.4058          | 0.915    |
| 0.012         | 35.0  | 3955 | 0.4433          | 0.92     |
| 0.0299        | 36.0  | 4068 | 0.4442          | 0.925    |
| 0.0206        | 37.0  | 4181 | 0.4736          | 0.92     |
| 0.0253        | 38.0  | 4294 | 0.5221          | 0.915    |
| 0.0147        | 39.0  | 4407 | 0.4488          | 0.92     |
| 0.0261        | 40.0  | 4520 | 0.4631          | 0.92     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
