Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: finetuned-for-YogaPosesv6
+  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-for-YogaPosesv6
+
+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: 0.0565
+- Accuracy: 0.9907
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use adamw_torch 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: 500
+- num_epochs: 12
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.9954        | 0.8772  | 100  | 0.8301          | 0.8505   |
+| 0.3505        | 1.7544  | 200  | 0.1881          | 0.9907   |
+| 0.1524        | 2.6316  | 300  | 0.0901          | 0.9844   |
+| 0.152         | 3.5088  | 400  | 0.1241          | 0.9688   |
+| 0.1314        | 4.3860  | 500  | 0.0562          | 0.9938   |
+| 0.1187        | 5.2632  | 600  | 0.1232          | 0.9720   |
+| 0.0936        | 6.1404  | 700  | 0.0893          | 0.9688   |
+| 0.0753        | 7.0175  | 800  | 0.1510          | 0.9626   |
+| 0.0155        | 7.8947  | 900  | 0.0536          | 0.9907   |
+| 0.0181        | 8.7719  | 1000 | 0.0515          | 0.9907   |
+| 0.0037        | 9.6491  | 1100 | 0.0570          | 0.9907   |
+| 0.0121        | 10.5263 | 1200 | 0.0570          | 0.9907   |
+| 0.0065        | 11.4035 | 1300 | 0.0565          | 0.9907   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

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": "Downdog",
+    "1": "Goddess",
+    "2": "Plank",
+    "3": "Tree",
+    "4": "Warrior2"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Downdog": "0",
+    "Goddess": "1",
+    "Plank": "2",
+    "Tree": "3",
+    "Warrior2": "4"
+  },
+  "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": "4.46.3"
+}

model.safetensors

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+size 343233204

training_args.bin

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