End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: ProteinClassificationModelV2
+  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. -->
+
+# ProteinClassificationModelV2
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4631
+- Accuracy: 0.92
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.707         | 1.0   | 113  | 0.3861          | 0.845    |
+| 0.3382        | 2.0   | 226  | 0.3137          | 0.87     |
+| 0.2635        | 3.0   | 339  | 0.2881          | 0.885    |
+| 0.2469        | 4.0   | 452  | 0.3090          | 0.88     |
+| 0.1995        | 5.0   | 565  | 0.2577          | 0.92     |
+| 0.1869        | 6.0   | 678  | 0.2783          | 0.91     |
+| 0.1799        | 7.0   | 791  | 0.2146          | 0.925    |
+| 0.1376        | 8.0   | 904  | 0.3013          | 0.89     |
+| 0.1079        | 9.0   | 1017 | 0.4004          | 0.885    |
+| 0.1207        | 10.0  | 1130 | 0.5334          | 0.85     |
+| 0.089         | 11.0  | 1243 | 0.3145          | 0.93     |
+| 0.1056        | 12.0  | 1356 | 0.3250          | 0.9      |
+| 0.1087        | 13.0  | 1469 | 0.4588          | 0.89     |
+| 0.0746        | 14.0  | 1582 | 0.3866          | 0.895    |
+| 0.081         | 15.0  | 1695 | 0.3356          | 0.905    |
+| 0.0539        | 16.0  | 1808 | 0.5468          | 0.89     |
+| 0.0772        | 17.0  | 1921 | 0.4060          | 0.895    |
+| 0.0729        | 18.0  | 2034 | 0.5682          | 0.875    |
+| 0.0525        | 19.0  | 2147 | 0.4364          | 0.905    |
+| 0.0654        | 20.0  | 2260 | 0.3860          | 0.895    |
+| 0.0461        | 21.0  | 2373 | 0.5711          | 0.895    |
+| 0.0539        | 22.0  | 2486 | 0.6325          | 0.89     |
+| 0.0309        | 23.0  | 2599 | 0.5805          | 0.885    |
+| 0.0452        | 24.0  | 2712 | 0.4380          | 0.905    |
+| 0.0406        | 25.0  | 2825 | 0.4316          | 0.9      |
+| 0.0404        | 26.0  | 2938 | 0.4540          | 0.905    |
+| 0.0288        | 27.0  | 3051 | 0.5276          | 0.915    |
+| 0.0493        | 28.0  | 3164 | 0.6025          | 0.895    |
+| 0.0244        | 29.0  | 3277 | 0.6028          | 0.9      |
+| 0.025         | 30.0  | 3390 | 0.5895          | 0.915    |
+| 0.0277        | 31.0  | 3503 | 0.4587          | 0.915    |
+| 0.0284        | 32.0  | 3616 | 0.4466          | 0.915    |
+| 0.029         | 33.0  | 3729 | 0.4343          | 0.905    |
+| 0.021         | 34.0  | 3842 | 0.4058          | 0.915    |
+| 0.012         | 35.0  | 3955 | 0.4433          | 0.92     |
+| 0.0299        | 36.0  | 4068 | 0.4442          | 0.925    |
+| 0.0206        | 37.0  | 4181 | 0.4736          | 0.92     |
+| 0.0253        | 38.0  | 4294 | 0.5221          | 0.915    |
+| 0.0147        | 39.0  | 4407 | 0.4488          | 0.92     |
+| 0.0261        | 40.0  | 4520 | 0.4631          | 0.92     |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0

config.json

@@ -0,0 +1,36 @@
+{
+  "_name_or_path": "google/vit-base-patch16-224",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "bend",
+    "1": "helix",
+    "2": "strand",
+    "3": "?"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "?": 3,
+    "bend": 0,
+    "helix": 1,
+    "strand": 2
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2"
+}

model.safetensors

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+oid sha256:9425f66ac7bb8c3d0f871cf95dd5e554b5b3ab351652319f00f30bc1baab1e51
+size 343230128

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": false,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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+size 4600