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mobilenet_v2_1.0_224-plant-disease-identification

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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7145092460881934
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  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 image_folder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3799
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- - Accuracy: 0.7145
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  ## Model description
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@@ -57,23 +57,26 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.3889 | 1.0 | 248 | 2.1952 | 0.6310 |
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- | 1.8202 | 2.0 | 496 | 1.6363 | 0.7013 |
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- | 1.6266 | 3.0 | 744 | 1.6291 | 0.6343 |
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- | 1.5566 | 4.0 | 992 | 1.3514 | 0.7129 |
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- | 1.5507 | 5.0 | 1240 | 1.3799 | 0.7145 |
 
 
 
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  ### Framework versions
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- - Transformers 4.26.1
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  - Pytorch 1.13.0
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  - Datasets 2.1.0
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  - Tokenizers 0.13.2
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7857752489331437
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  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 image_folder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0461
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+ - Accuracy: 0.7858
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.15
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+ - num_epochs: 8
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.9265 | 1.0 | 248 | 2.7159 | 0.4703 |
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+ | 1.9734 | 2.0 | 496 | 1.7668 | 0.6649 |
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+ | 1.7206 | 3.0 | 744 | 1.4012 | 0.7206 |
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+ | 1.6406 | 4.0 | 992 | 1.2514 | 0.7644 |
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+ | 1.6075 | 5.0 | 1240 | 1.2934 | 0.7094 |
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+ | 1.5932 | 6.0 | 1488 | 1.2093 | 0.7257 |
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+ | 1.5203 | 7.0 | 1736 | 1.0461 | 0.7858 |
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+ | 1.5076 | 8.0 | 1984 | 1.0580 | 0.7848 |
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  ### Framework versions
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+ - Transformers 4.27.3
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  - Pytorch 1.13.0
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  - Datasets 2.1.0
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  - Tokenizers 0.13.2