32health/non-ada-classification

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/dinov2-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: outputs_Feb_2026
+  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. -->
+
+# outputs_Feb_2026
+
+This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0353
+- Precision: 0.9789
+- Recall: 0.9769
+- F1: 0.9779
+
+## 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: 5e-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 0.1
+- num_epochs: 8
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.4174        | 1.0   | 145  | 0.0736          | 0.9245    | 0.9139 | 0.9192 |
+| 0.2111        | 2.0   | 290  | 0.0321          | 0.9615    | 0.9716 | 0.9666 |
+| 0.0776        | 3.0   | 435  | 0.0303          | 0.9667    | 0.9748 | 0.9707 |
+| 0.0637        | 4.0   | 580  | 0.0316          | 0.9738    | 0.9769 | 0.9754 |
+| 0.0401        | 5.0   | 725  | 0.0322          | 0.9850    | 0.9664 | 0.9756 |
+| 0.0138        | 6.0   | 870  | 0.0357          | 0.9799    | 0.9716 | 0.9757 |
+| 0.0449        | 7.0   | 1015 | 0.0391          | 0.9799    | 0.9748 | 0.9774 |
+| 0.0008        | 8.0   | 1160 | 0.0353          | 0.9789    | 0.9769 | 0.9779 |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.5.0
+- Tokenizers 0.22.2

config.json

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+{
+  "apply_layernorm": true,
+  "architectures": [
+    "Dinov2ForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "drop_path_rate": 0.0,
+  "dtype": "float32",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Pano",
+    "1": "FMX",
+    "2": "BW",
+    "3": "PA",
+    "4": "PC",
+    "5": "IOP",
+    "6": "Photo",
+    "7": "NA"
+  },
+  "image_size": 518,
+  "initializer_range": 0.02,
+  "label2id": {
+    "BW": 2,
+    "FMX": 1,
+    "IOP": 5,
+    "NA": 7,
+    "PA": 3,
+    "PC": 4,
+    "Pano": 0,
+    "Photo": 6
+  },
+  "layer_norm_eps": 1e-06,
+  "layerscale_value": 1.0,
+  "mlp_ratio": 4,
+  "model_type": "dinov2",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "out_features": [
+    "stage12"
+  ],
+  "out_indices": [
+    12
+  ],
+  "patch_size": 14,
+  "problem_type": "multi_label_classification",
+  "qkv_bias": true,
+  "reshape_hidden_states": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4",
+    "stage5",
+    "stage6",
+    "stage7",
+    "stage8",
+    "stage9",
+    "stage10",
+    "stage11",
+    "stage12"
+  ],
+  "transformers_version": "5.0.0",
+  "use_cache": false,
+  "use_mask_token": true,
+  "use_swiglu_ffn": false
+}

model.safetensors

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+oid sha256:cf71e37becf341923fb7011fd851669407086111825b07771802ff113953647d
+size 346396816

preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "data_format": "channels_first",
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "BitImageProcessorFast",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 256
+  }
+}

training_args.bin

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+size 5201