File size: 2,552 Bytes
19a72c6 |
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 |
---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Expert1-leaf-disease-convnextv2-base-22k-224-0_4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8337874659400545
---
<!-- 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. -->
# Expert1-leaf-disease-convnextv2-base-22k-224-0_4
This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3647
- Accuracy: 0.8338
## 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: 5e-05
- train_batch_size: 300
- eval_batch_size: 300
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 16
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.73 | 2 | 1.4423 | 0.3842 |
| No log | 1.82 | 5 | 0.6525 | 0.6921 |
| No log | 2.91 | 8 | 0.4914 | 0.7466 |
| 0.9097 | 4.0 | 11 | 0.4710 | 0.7793 |
| 0.9097 | 4.73 | 13 | 0.4358 | 0.8011 |
| 0.9097 | 5.82 | 16 | 0.4048 | 0.8174 |
| 0.9097 | 6.91 | 19 | 0.3875 | 0.8229 |
| 0.3808 | 8.0 | 22 | 0.3756 | 0.8365 |
| 0.3808 | 8.73 | 24 | 0.3794 | 0.8229 |
| 0.3808 | 9.82 | 27 | 0.3701 | 0.8283 |
| 0.3221 | 10.91 | 30 | 0.3659 | 0.8338 |
| 0.3221 | 11.64 | 32 | 0.3647 | 0.8338 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
|