A2H0H0R1's picture
Model save
f63fb75
|
raw
history blame
2.14 kB
---
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: mobilenet_v2_1.0_224-plant-disease2
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: 0.9638691322901849
---
<!-- 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. -->
# mobilenet_v2_1.0_224-plant-disease2
This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1510
- Accuracy: 0.9639
## 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: 100
- eval_batch_size: 100
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 400
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2171 | 1.0 | 158 | 1.0595 | 0.8188 |
| 0.4082 | 2.0 | 316 | 0.3154 | 0.9387 |
| 0.295 | 3.0 | 474 | 0.2191 | 0.9555 |
| 0.2266 | 4.0 | 633 | 0.1747 | 0.9595 |
| 0.2168 | 5.0 | 791 | 0.2135 | 0.9499 |
| 0.2091 | 5.99 | 948 | 0.1510 | 0.9639 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0