focia/yt-grader

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- image-classification
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: yt-grader-model
+  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. -->
+
+# yt-grader-model
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the yt-thumbnail-dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4270
+- Accuracy: 0.8431
+
+## 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-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4166        | 1.0   | 442  | 0.4169          | 0.8079   |
+| 0.2478        | 2.0   | 884  | 0.3685          | 0.8395   |
+| 0.1407        | 3.0   | 1326 | 0.4270          | 0.8431   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1
+- Datasets 2.14.4
+- Tokenizers 0.13.3

all_results.json

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.8431400282885432,
+    "eval_loss": 0.4270206689834595,
+    "eval_runtime": 202.7777,
+    "eval_samples_per_second": 34.866,
+    "eval_steps_per_second": 2.18
+}

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,
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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": "4.32.0"
+}

eval_results.json

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.8431400282885432,
+    "eval_loss": 0.4270206689834595,
+    "eval_runtime": 202.7777,
+    "eval_samples_per_second": 34.866,
+    "eval_steps_per_second": 2.18
+}

preprocessor_config.json

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

pytorch_model.bin

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+size 343268717

training_args.bin

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