File size: 3,490 Bytes
25211c3 |
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 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
---
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
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: 1.0
---
<!-- 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
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: 0.0004
- Accuracy: 1.0
## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 4
- 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 | 90 | 0.1145 | 0.9777 |
| No log | 2.0 | 180 | 0.0646 | 0.9732 |
| No log | 3.0 | 270 | 0.0524 | 0.9821 |
| No log | 4.0 | 360 | 0.0144 | 0.9955 |
| No log | 5.0 | 450 | 0.0234 | 0.9911 |
| 0.3541 | 6.0 | 540 | 0.0189 | 0.9911 |
| 0.3541 | 7.0 | 630 | 0.0099 | 0.9955 |
| 0.3541 | 8.0 | 720 | 0.0253 | 0.9866 |
| 0.3541 | 9.0 | 810 | 0.0414 | 0.9866 |
| 0.3541 | 10.0 | 900 | 0.0034 | 1.0 |
| 0.3541 | 11.0 | 990 | 0.0099 | 0.9955 |
| 0.2485 | 12.0 | 1080 | 0.0004 | 1.0 |
| 0.2485 | 13.0 | 1170 | 0.0088 | 0.9955 |
| 0.2485 | 14.0 | 1260 | 0.0104 | 0.9955 |
| 0.2485 | 15.0 | 1350 | 0.0001 | 1.0 |
| 0.2485 | 16.0 | 1440 | 0.0098 | 0.9955 |
| 0.2229 | 17.0 | 1530 | 0.0002 | 1.0 |
| 0.2229 | 18.0 | 1620 | 0.0004 | 1.0 |
| 0.2229 | 19.0 | 1710 | 0.0002 | 1.0 |
| 0.2229 | 20.0 | 1800 | 0.0001 | 1.0 |
| 0.2229 | 21.0 | 1890 | 0.0005 | 1.0 |
| 0.2229 | 22.0 | 1980 | 0.0002 | 1.0 |
| 0.2192 | 23.0 | 2070 | 0.0006 | 1.0 |
| 0.2192 | 24.0 | 2160 | 0.0001 | 1.0 |
| 0.2192 | 25.0 | 2250 | 0.0013 | 1.0 |
| 0.2192 | 26.0 | 2340 | 0.0002 | 1.0 |
| 0.2192 | 27.0 | 2430 | 0.0002 | 1.0 |
| 0.211 | 28.0 | 2520 | 0.0012 | 1.0 |
| 0.211 | 29.0 | 2610 | 0.0013 | 1.0 |
| 0.211 | 30.0 | 2700 | 0.0004 | 1.0 |
### Framework versions
- Transformers 4.38.1
- Pytorch 1.10.0+cu111
- Datasets 2.17.1
- Tokenizers 0.15.2
|