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aaa12963337
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msi-nat-mini

Image Classification
Transformers
Safetensors
nat
Generated from Trainer
Eval Results
Inference Endpoints
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End of training

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  1. README.md +19 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -23,16 +23,16 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8460220784164446
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  - name: F1
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  type: f1
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- value: 0.8017318846499469
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  - name: Precision
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  type: precision
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- value: 0.8296559303406882
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  - name: Recall
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  type: recall
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- value: 0.7756263336758081
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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
@@ -42,11 +42,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3451
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- - Accuracy: 0.8460
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- - F1: 0.8017
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- - Precision: 0.8297
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- - Recall: 0.7756
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  ## Model description
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@@ -80,16 +80,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.5705 | 1.0 | 1970 | 0.5230 | 0.7410 | 0.6588 | 0.6988 | 0.6232 |
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- | 0.4805 | 2.0 | 3941 | 0.4447 | 0.7924 | 0.7298 | 0.7640 | 0.6986 |
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- | 0.4521 | 3.0 | 5911 | 0.4090 | 0.8107 | 0.7518 | 0.7936 | 0.7141 |
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- | 0.4343 | 4.0 | 7882 | 0.3878 | 0.8239 | 0.7768 | 0.7907 | 0.7634 |
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- | 0.4003 | 5.0 | 9852 | 0.3720 | 0.8328 | 0.7850 | 0.8113 | 0.7604 |
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- | 0.3887 | 6.0 | 11823 | 0.3620 | 0.8376 | 0.7875 | 0.8295 | 0.7496 |
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- | 0.3709 | 7.0 | 13793 | 0.3506 | 0.8435 | 0.7977 | 0.8286 | 0.7690 |
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- | 0.3686 | 8.0 | 15764 | 0.3473 | 0.8461 | 0.8025 | 0.8271 | 0.7793 |
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- | 0.3819 | 9.0 | 17734 | 0.3422 | 0.8476 | 0.8052 | 0.8270 | 0.7845 |
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- | 0.3838 | 10.0 | 19700 | 0.3451 | 0.8460 | 0.8017 | 0.8297 | 0.7756 |
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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: 0.6308708414872799
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  - name: F1
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  type: f1
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+ value: 0.47632740072381147
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  - name: Precision
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  type: precision
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+ value: 0.6193914388860238
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  - name: Recall
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  type: recall
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+ value: 0.3869512686266613
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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 was trained from scratch on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8600
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+ - Accuracy: 0.6309
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+ - F1: 0.4763
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+ - Precision: 0.6194
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+ - Recall: 0.3870
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.5496 | 1.0 | 2015 | 0.7573 | 0.5955 | 0.4196 | 0.5559 | 0.3369 |
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+ | 0.4807 | 2.0 | 4031 | 0.7416 | 0.6309 | 0.4981 | 0.6074 | 0.4222 |
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+ | 0.4235 | 3.0 | 6047 | 0.7680 | 0.6325 | 0.5047 | 0.6076 | 0.4317 |
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+ | 0.3879 | 4.0 | 8063 | 0.7875 | 0.6339 | 0.4923 | 0.6179 | 0.4092 |
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+ | 0.3702 | 5.0 | 10078 | 0.7923 | 0.6383 | 0.5128 | 0.6168 | 0.4388 |
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+ | 0.3568 | 6.0 | 12094 | 0.8311 | 0.6313 | 0.4969 | 0.6090 | 0.4197 |
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+ | 0.3661 | 7.0 | 14110 | 0.8345 | 0.6316 | 0.4843 | 0.6166 | 0.3987 |
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+ | 0.354 | 8.0 | 16126 | 0.8501 | 0.6305 | 0.4800 | 0.6162 | 0.3931 |
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+ | 0.3569 | 9.0 | 18141 | 0.8552 | 0.6318 | 0.4809 | 0.6193 | 0.3931 |
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+ | 0.3536 | 10.0 | 20150 | 0.8600 | 0.6309 | 0.4763 | 0.6194 | 0.3870 |
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  ### Framework versions
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