End of training

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+- f1
+model-index:
+- name: 3class_EfficientFormer30M_ForTesting
+  results: []
+---
+
+<!-- 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. -->
+
+# 3class_EfficientFormer30M_ForTesting
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0820
+- Precision: 0.9831
+- Recall: 0.9790
+- Accuracy: 0.9844
+- F1: 0.9809
+- Roc Auc: 0.9981
+
+## 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: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | Accuracy | F1     | Roc Auc |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|:-------:|
+| 0.1609        | 0.3436 | 200  | 0.0851          | 0.9673    | 0.9645 | 0.9718   | 0.9658 | 0.9964  |
+| 0.0811        | 0.6873 | 400  | 0.0652          | 0.9767    | 0.9725 | 0.9790   | 0.9745 | 0.9981  |
+| 0.0418        | 1.0309 | 600  | 0.1268          | 0.9602    | 0.9661 | 0.9690   | 0.9628 | 0.9948  |
+| 0.0427        | 1.3746 | 800  | 0.0735          | 0.9756    | 0.9744 | 0.9793   | 0.9750 | 0.9973  |
+| 0.0054        | 1.7182 | 1000 | 0.0614          | 0.9823    | 0.9779 | 0.9834   | 0.9800 | 0.9982  |
+| 0.0293        | 2.0619 | 1200 | 0.0681          | 0.9812    | 0.9788 | 0.9834   | 0.9800 | 0.9983  |
+| 0.0020        | 2.4055 | 1400 | 0.0676          | 0.9818    | 0.9787 | 0.9837   | 0.9802 | 0.9984  |
+| 0.0332        | 2.7491 | 1600 | 0.0818          | 0.9812    | 0.9759 | 0.9823   | 0.9784 | 0.9982  |
+| 0.0005        | 3.0928 | 1800 | 0.0755          | 0.9824    | 0.9793 | 0.9841   | 0.9808 | 0.9982  |
+| 0.0017        | 3.4364 | 2000 | 0.0842          | 0.9819    | 0.9775 | 0.9832   | 0.9796 | 0.9979  |
+| 0.0049        | 3.7801 | 2200 | 0.0820          | 0.9831    | 0.9790 | 0.9844   | 0.9809 | 0.9981  |
+
+
+### Framework versions
+
+- Transformers 5.3.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

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+{
+  "architectures": [
+    "UniversalVisionModel"
+  ],
+  "auto_map": {
+    "AutoConfig": "modeling_universal_vision.UniversalVisionConfig",
+    "AutoModelForImageClassification": "modeling_universal_vision.UniversalVisionModel"
+  },
+  "backbone_name": "efficientformer_l3.snap_dist_in1k",
+  "dtype": "float32",
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "model_type": "universal_vision",
+  "pretrained": true,
+  "transformers_version": "5.3.0",
+  "use_cache": false
+}

model.safetensors

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+oid sha256:393bd050c762da978db232c61c525527a22b12a773c87e9a328f9177ff945c4e
+size 121893600

training_args.bin

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+size 5265