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segformer-b0-finetuned-pokemon

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@@ -12,14 +12,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # segformer-b0-finetuned-pokemon
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- This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0298
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- - Mean Iou: 0.4971
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- - Mean Accuracy: 0.9941
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- - Overall Accuracy: 0.9941
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- - Per Category Iou: [0.0, 0.99410193702663]
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- - Per Category Accuracy: [nan, 0.99410193702663]
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  ## Model description
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@@ -44,23 +44,18 @@ 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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- - num_epochs: 50
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------------:|:-------------------------:|
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- | 0.0286 | 40.0 | 1160 | 0.0304 | 0.4965 | 0.9929 | 0.9929 | [0.0, 0.9929262067682688] | [nan, 0.9929262067682688] |
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- | 0.0272 | 41.0 | 1189 | 0.0301 | 0.4966 | 0.9933 | 0.9933 | [0.0, 0.9932505252321254] | [nan, 0.9932505252321254] |
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- | 0.0279 | 42.0 | 1218 | 0.0305 | 0.4973 | 0.9947 | 0.9947 | [0.0, 0.994698129326027] | [nan, 0.994698129326027] |
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- | 0.0309 | 43.0 | 1247 | 0.0295 | 0.4966 | 0.9931 | 0.9931 | [0.0, 0.9931164081595019] | [nan, 0.9931164081595019] |
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- | 0.028 | 44.0 | 1276 | 0.0294 | 0.4967 | 0.9934 | 0.9934 | [0.0, 0.9933975466612431] | [nan, 0.9933975466612431] |
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- | 0.0276 | 45.0 | 1305 | 0.0298 | 0.4970 | 0.9941 | 0.9941 | [0.0, 0.994062837929389] | [nan, 0.994062837929389] |
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- | 0.0281 | 46.0 | 1334 | 0.0300 | 0.4969 | 0.9939 | 0.9939 | [0.0, 0.9938931511561724] | [nan, 0.9938931511561724] |
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- | 0.0273 | 47.0 | 1363 | 0.0297 | 0.4968 | 0.9936 | 0.9936 | [0.0, 0.993593207587916] | [nan, 0.993593207587916] |
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- | 0.0291 | 48.0 | 1392 | 0.0297 | 0.4970 | 0.9941 | 0.9941 | [0.0, 0.9940591430922732] | [nan, 0.9940591430922732] |
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- | 0.0269 | 49.0 | 1421 | 0.0294 | 0.4968 | 0.9936 | 0.9936 | [0.0, 0.9936409647363091] | [nan, 0.9936409647363091] |
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- | 0.0279 | 50.0 | 1450 | 0.0298 | 0.4971 | 0.9941 | 0.9941 | [0.0, 0.99410193702663] | [nan, 0.99410193702663] |
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  ### Framework versions
 
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  # segformer-b0-finetuned-pokemon
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+ This model is a fine-tuned version of [ydmeira/segformer-b0-finetuned-pokemon](https://huggingface.co/ydmeira/segformer-b0-finetuned-pokemon) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0225
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+ - Mean Accuracy: 0.9927
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+ - Mean Iou: 0.4964
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+ - Overall Accuracy: 0.9927
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+ - Per Category Accuracy: [nan, 0.9927247002783977]
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+ - Per Category Iou: [0.0, 0.9927247002783977]
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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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+ - num_epochs: 20
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Accuracy | Mean Iou | Overall Accuracy | Per Category Accuracy | Per Category Iou |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------:|:--------:|:----------------:|:-------------------------:|:-------------------------:|
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+ | 0.0217 | 15.0 | 435 | 0.0228 | 0.9944 | 0.4972 | 0.9944 | [nan, 0.9944285716570368] | [0.0, 0.9944285716570368] |
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+ | 0.0228 | 16.0 | 464 | 0.0227 | 0.9943 | 0.4971 | 0.9943 | [nan, 0.9942943994375907] | [0.0, 0.9942943994375907] |
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+ | 0.0204 | 17.0 | 493 | 0.0226 | 0.9933 | 0.4967 | 0.9933 | [nan, 0.9933366094222428] | [0.0, 0.9933366094222428] |
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+ | 0.0202 | 18.0 | 522 | 0.0226 | 0.9929 | 0.4964 | 0.9929 | [nan, 0.9928635048309444] | [0.0, 0.9928635048309444] |
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+ | 0.021 | 19.0 | 551 | 0.0226 | 0.9924 | 0.4962 | 0.9924 | [nan, 0.9924163192462797] | [0.0, 0.9924163192462797] |
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+ | 0.0203 | 20.0 | 580 | 0.0225 | 0.9927 | 0.4964 | 0.9927 | [nan, 0.9927247002783977] | [0.0, 0.9927247002783977] |
 
 
 
 
 
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  ### Framework versions