File size: 2,396 Bytes
d2ea7e2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_3Class_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8489055533036076
---
<!-- 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. -->
# Karma_3Class_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold4
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5710
- Accuracy: 0.8489
## 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: 0.0001
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3726 | 1.0 | 2468 | 0.3949 | 0.8399 |
| 0.325 | 2.0 | 4936 | 0.4383 | 0.8328 |
| 0.2727 | 3.0 | 7404 | 0.4165 | 0.8467 |
| 0.067 | 4.0 | 9872 | 0.6221 | 0.8448 |
| 0.0057 | 5.0 | 12340 | 1.0252 | 0.8438 |
| 0.0004 | 6.0 | 14808 | 1.0541 | 0.8462 |
| 0.0155 | 7.0 | 17276 | 1.3852 | 0.8511 |
| 0.0047 | 8.0 | 19744 | 1.4084 | 0.8509 |
| 0.0007 | 9.0 | 22212 | 1.5540 | 0.8503 |
| 0.0 | 10.0 | 24680 | 1.5710 | 0.8489 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
|