|
---
|
|
library_name: transformers
|
|
license: apache-2.0
|
|
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
|
|
tags:
|
|
- generated_from_trainer
|
|
metrics:
|
|
- precision
|
|
- recall
|
|
- f1
|
|
- accuracy
|
|
model-index:
|
|
- name: beit-base-patch16-224-pt22k-ft22k-finetuned-barkley
|
|
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. -->
|
|
|
|
# beit-base-patch16-224-pt22k-ft22k-finetuned-barkley
|
|
|
|
This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.0079
|
|
- Precision: 1.0
|
|
- Recall: 1.0
|
|
- F1: 1.0
|
|
- Accuracy: 1.0
|
|
- Top1 Accuracy: 1.0
|
|
- Error Rate: 0.0
|
|
|
|
## 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: 0.0002
|
|
- train_batch_size: 32
|
|
- eval_batch_size: 32
|
|
- seed: 42
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
|
- lr_scheduler_type: linear
|
|
- lr_scheduler_warmup_ratio: 0.1
|
|
- num_epochs: 30
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Top1 Accuracy | Error Rate |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
|
|
| 1.5547 | 1.0 | 38 | 1.4018 | 0.5683 | 0.4539 | 0.4240 | 0.4728 | 0.4539 | 0.5272 |
|
|
| 1.1732 | 2.0 | 76 | 0.9193 | 0.8095 | 0.7961 | 0.7985 | 0.8077 | 0.7961 | 0.1923 |
|
|
| 0.6764 | 3.0 | 114 | 0.3644 | 0.9488 | 0.9474 | 0.9470 | 0.9483 | 0.9474 | 0.0517 |
|
|
| 0.2566 | 4.0 | 152 | 0.0871 | 0.9937 | 0.9934 | 0.9934 | 0.9944 | 0.9934 | 0.0056 |
|
|
| 0.1014 | 5.0 | 190 | 0.0533 | 0.9809 | 0.9803 | 0.9802 | 0.9811 | 0.9803 | 0.0189 |
|
|
| 0.0538 | 6.0 | 228 | 0.0208 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
|
|
| 0.0304 | 7.0 | 266 | 0.0079 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
|
|
| 0.0571 | 8.0 | 304 | 0.0088 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
|
|
| 0.0608 | 9.0 | 342 | 0.0226 | 0.9936 | 0.9934 | 0.9934 | 0.9933 | 0.9934 | 0.0067 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.44.2
|
|
- Pytorch 2.3.1+cu121
|
|
- Datasets 3.0.1
|
|
- Tokenizers 0.19.1
|
|
|
