End of training

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+- f1
+model-index:
+- name: global_effformerv2_s2
+  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. -->
+
+# global_effformerv2_s2
+
+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: 0.0634
+- Precision: 0.9798
+- Recall: 0.9761
+- Accuracy: 0.9818
+- F1: 0.9779
+- Roc Auc: 0.9983
+
+## 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
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | Accuracy | F1     | Roc Auc |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|:-------:|
+| 0.1269        | 0.3436 | 200  | 0.2372          | 0.9396    | 0.9473 | 0.9517   | 0.9427 | 0.9935  |
+| 0.0940        | 0.6873 | 400  | 0.0662          | 0.9748    | 0.9710 | 0.9776   | 0.9728 | 0.9978  |
+| 0.0869        | 1.0309 | 600  | 0.0805          | 0.9696    | 0.9675 | 0.9741   | 0.9685 | 0.9968  |
+| 0.0401        | 1.3746 | 800  | 0.0649          | 0.9753    | 0.9742 | 0.9793   | 0.9748 | 0.9980  |
+| 0.0455        | 1.7182 | 1000 | 0.0634          | 0.9798    | 0.9761 | 0.9818   | 0.9779 | 0.9983  |
+| 0.0431        | 2.0619 | 1200 | 6.0823          | 0.9765    | 0.9771 | 0.9807   | 0.9768 | 0.9975  |
+| 0.0259        | 2.4055 | 1400 | 0.0664          | 0.9802    | 0.9785 | 0.9830   | 0.9793 | 0.9983  |
+| 0.0219        | 2.7491 | 1600 | 0.0703          | 0.9799    | 0.9760 | 0.9818   | 0.9779 | 0.9982  |
+| 0.0128        | 3.0928 | 1800 | 0.0659          | 0.9797    | 0.9792 | 0.9830   | 0.9795 | 0.9982  |
+| 0.0053        | 3.4364 | 2000 | 0.0667          | 0.9817    | 0.9792 | 0.9839   | 0.9804 | 0.9983  |
+| 0.0045        | 3.7801 | 2200 | 0.0697          | 0.9809    | 0.9773 | 0.9828   | 0.9790 | 0.9982  |
+
+
+### Framework versions
+
+- Transformers 5.3.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.7.0
+- 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": "efficientformerv2_s2.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:de5d2f19cd7b4bf1d2a4acd0191d97469497e781b1e7db2a1f45ad7a71285ea3
+size 49145824

training_args.bin

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+oid sha256:14a00fdbe69acbdb95eb7d39d2e7962376b837970643608fdef6b26c099600d8
+size 5265