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---
license: apache-2.0
base_model: microsoft/cvt-21-384-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cvt-21-384-22k-finetuned-PinnatelyCompound
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9955357142857143
---
<!-- 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. -->
# cvt-21-384-22k-finetuned-PinnatelyCompound
This model is a fine-tuned version of [microsoft/cvt-21-384-22k](https://huggingface.co/microsoft/cvt-21-384-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0064
- Accuracy: 0.9955
## 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: 40
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 23 | 0.2918 | 0.8973 |
| No log | 2.0 | 46 | 0.1656 | 0.9330 |
| No log | 3.0 | 69 | 0.0529 | 0.9821 |
| No log | 4.0 | 92 | 0.0144 | 0.9955 |
| No log | 5.0 | 115 | 0.0266 | 0.9911 |
| No log | 6.0 | 138 | 0.0244 | 0.9955 |
| No log | 7.0 | 161 | 0.0144 | 0.9955 |
| No log | 8.0 | 184 | 0.0154 | 0.9955 |
| No log | 9.0 | 207 | 0.0188 | 0.9911 |
| No log | 10.0 | 230 | 0.0094 | 0.9955 |
| No log | 11.0 | 253 | 0.0055 | 1.0 |
| No log | 12.0 | 276 | 0.0026 | 1.0 |
| No log | 13.0 | 299 | 0.0057 | 1.0 |
| No log | 14.0 | 322 | 0.0079 | 0.9955 |
| No log | 15.0 | 345 | 0.0026 | 1.0 |
| No log | 16.0 | 368 | 0.0017 | 1.0 |
| No log | 17.0 | 391 | 0.0044 | 0.9955 |
| No log | 18.0 | 414 | 0.0038 | 1.0 |
| No log | 19.0 | 437 | 0.0120 | 0.9911 |
| No log | 20.0 | 460 | 0.0005 | 1.0 |
| No log | 21.0 | 483 | 0.0019 | 1.0 |
| 0.2553 | 22.0 | 506 | 0.0020 | 1.0 |
| 0.2553 | 23.0 | 529 | 0.0026 | 1.0 |
| 0.2553 | 24.0 | 552 | 0.0053 | 0.9955 |
| 0.2553 | 25.0 | 575 | 0.0009 | 1.0 |
| 0.2553 | 26.0 | 598 | 0.0008 | 1.0 |
| 0.2553 | 27.0 | 621 | 0.0016 | 1.0 |
| 0.2553 | 28.0 | 644 | 0.0010 | 1.0 |
| 0.2553 | 29.0 | 667 | 0.0008 | 1.0 |
| 0.2553 | 30.0 | 690 | 0.0064 | 0.9955 |
### Framework versions
- Transformers 4.38.1
- Pytorch 1.10.0+cu111
- Datasets 2.17.1
- Tokenizers 0.15.2
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