End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: finetuned-mango-types
+  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. -->
+
+# finetuned-mango-types
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5751
+- Accuracy: 0.9292
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9926        | 1.0   | 22   | 1.9526          | 0.3833   |
+| 1.7976        | 2.0   | 44   | 1.7500          | 0.6083   |
+| 1.5678        | 3.0   | 66   | 1.5025          | 0.7583   |
+| 1.3907        | 4.0   | 88   | 1.2804          | 0.9      |
+| 1.0873        | 5.0   | 110  | 1.1005          | 0.9042   |
+| 0.9511        | 6.0   | 132  | 1.0130          | 0.8875   |
+| 0.8476        | 7.0   | 154  | 0.9424          | 0.8833   |
+| 0.7511        | 8.0   | 176  | 0.8325          | 0.9042   |
+| 0.6985        | 9.0   | 198  | 0.7894          | 0.9083   |
+| 0.6515        | 10.0  | 220  | 0.8052          | 0.8792   |
+| 0.5775        | 11.0  | 242  | 0.7600          | 0.8792   |
+| 0.5458        | 12.0  | 264  | 0.6684          | 0.925    |
+| 0.5331        | 13.0  | 286  | 0.7148          | 0.8917   |
+| 0.4823        | 14.0  | 308  | 0.6849          | 0.9125   |
+| 0.4579        | 15.0  | 330  | 0.6414          | 0.9167   |
+| 0.4435        | 16.0  | 352  | 0.6557          | 0.8833   |
+| 0.4411        | 17.0  | 374  | 0.5968          | 0.9083   |
+| 0.453         | 18.0  | 396  | 0.5751          | 0.9292   |
+| 0.445         | 19.0  | 418  | 0.6035          | 0.9083   |
+| 0.4357        | 20.0  | 440  | 0.6010          | 0.9083   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

all_results.json

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+    "eval_steps_per_second": 1.262,
+    "total_flos": 2.1078954658234368e+18,
+    "train_loss": 0.8308919093825601,
+    "train_runtime": 956.1106,
+    "train_samples_per_second": 28.449,
+    "train_steps_per_second": 0.46
+}

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Anwar Ratool",
+    "1": "Chaunsa (Black)",
+    "2": "Chaunsa (Summer Bahisht)",
+    "3": "Chaunsa (White)",
+    "4": "Dosehri",
+    "5": "Fajri",
+    "6": "Langra",
+    "7": "Sindhri"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Anwar Ratool": 0,
+    "Chaunsa (Black)": 1,
+    "Chaunsa (Summer Bahisht)": 2,
+    "Chaunsa (White)": 3,
+    "Dosehri": 4,
+    "Fajri": 5,
+    "Langra": 6,
+    "Sindhri": 7
+  },
+  "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": "4.38.1"
+}

eval_results.json

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+}

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preprocessor_config.json

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runs/Mar14_05-27-08_d0d63f61dcf5/events.out.tfevents.1710394030.d0d63f61dcf5.34.0

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train_results.json

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