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carolinetfls
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plant-seedlings-model-ConvNet

Image Classification
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convnext
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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: 0.9598726114649682
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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 [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2134
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- - Accuracy: 0.9599
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  ## Model description
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@@ -64,31 +64,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.4223 | 0.8 | 100 | 0.2878 | 0.9140 |
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- | 0.2957 | 1.6 | 200 | 0.2490 | 0.9204 |
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- | 0.0884 | 2.4 | 300 | 0.2440 | 0.9293 |
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- | 0.0534 | 3.2 | 400 | 0.2140 | 0.9350 |
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- | 0.0067 | 4.0 | 500 | 0.1659 | 0.9554 |
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- | 0.0038 | 4.8 | 600 | 0.1950 | 0.9548 |
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- | 0.0061 | 5.6 | 700 | 0.1658 | 0.9618 |
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- | 0.0029 | 6.4 | 800 | 0.1793 | 0.9599 |
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- | 0.0004 | 7.2 | 900 | 0.2021 | 0.9592 |
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- | 0.0003 | 8.0 | 1000 | 0.2115 | 0.9561 |
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- | 0.0004 | 8.8 | 1100 | 0.2106 | 0.9561 |
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- | 0.0002 | 9.6 | 1200 | 0.1929 | 0.9605 |
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- | 0.0003 | 10.4 | 1300 | 0.2311 | 0.9548 |
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- | 0.0002 | 11.2 | 1400 | 0.2091 | 0.9605 |
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- | 0.0002 | 12.0 | 1500 | 0.2076 | 0.9586 |
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- | 0.0001 | 12.8 | 1600 | 0.2084 | 0.9592 |
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- | 0.0002 | 13.6 | 1700 | 0.2094 | 0.9605 |
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- | 0.0001 | 14.4 | 1800 | 0.2104 | 0.9592 |
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- | 0.0001 | 15.2 | 1900 | 0.2111 | 0.9592 |
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- | 0.0001 | 16.0 | 2000 | 0.2117 | 0.9592 |
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- | 0.0001 | 16.8 | 2100 | 0.2123 | 0.9592 |
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- | 0.0001 | 17.6 | 2200 | 0.2128 | 0.9599 |
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- | 0.0001 | 18.4 | 2300 | 0.2131 | 0.9599 |
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- | 0.0001 | 19.2 | 2400 | 0.2134 | 0.9599 |
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- | 0.0001 | 20.0 | 2500 | 0.2134 | 0.9599 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9522292993630573
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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 [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2410
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+ - Accuracy: 0.9522
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.494 | 0.8 | 100 | 0.4274 | 0.8828 |
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+ | 0.246 | 1.6 | 200 | 0.2878 | 0.8930 |
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+ | 0.1042 | 2.4 | 300 | 0.2227 | 0.9172 |
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+ | 0.0174 | 3.2 | 400 | 0.2208 | 0.9299 |
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+ | 0.0088 | 4.0 | 500 | 0.3197 | 0.9185 |
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+ | 0.0078 | 4.8 | 600 | 0.2555 | 0.9357 |
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+ | 0.0013 | 5.6 | 700 | 0.2599 | 0.9427 |
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+ | 0.0068 | 6.4 | 800 | 0.3072 | 0.9312 |
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+ | 0.0007 | 7.2 | 900 | 0.2217 | 0.9484 |
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+ | 0.0004 | 8.0 | 1000 | 0.2551 | 0.9401 |
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+ | 0.0003 | 8.8 | 1100 | 0.2321 | 0.9478 |
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+ | 0.0002 | 9.6 | 1200 | 0.2329 | 0.9484 |
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+ | 0.0002 | 10.4 | 1300 | 0.2322 | 0.9478 |
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+ | 0.0002 | 11.2 | 1400 | 0.2342 | 0.9478 |
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+ | 0.0002 | 12.0 | 1500 | 0.2348 | 0.9490 |
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+ | 0.0001 | 12.8 | 1600 | 0.2358 | 0.9490 |
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+ | 0.0001 | 13.6 | 1700 | 0.2368 | 0.9497 |
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+ | 0.0001 | 14.4 | 1800 | 0.2377 | 0.9510 |
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+ | 0.0001 | 15.2 | 1900 | 0.2384 | 0.9516 |
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+ | 0.0001 | 16.0 | 2000 | 0.2391 | 0.9516 |
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+ | 0.0001 | 16.8 | 2100 | 0.2397 | 0.9522 |
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+ | 0.0001 | 17.6 | 2200 | 0.2401 | 0.9522 |
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+ | 0.0001 | 18.4 | 2300 | 0.2406 | 0.9522 |
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+ | 0.0001 | 19.2 | 2400 | 0.2409 | 0.9522 |
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+ | 0.0001 | 20.0 | 2500 | 0.2410 | 0.9522 |
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  ### Framework versions