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End of training

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  1. README.md +95 -0
  2. config.json +60 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +28 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: Boya1_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold3
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8222402597402597
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Boya1_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold3
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.8476
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+ - Accuracy: 0.8222
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.4509 | 1.0 | 923 | 0.4494 | 0.8149 |
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+ | 0.3482 | 2.0 | 1846 | 0.4215 | 0.8328 |
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+ | 0.2766 | 3.0 | 2769 | 0.4845 | 0.8241 |
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+ | 0.1282 | 4.0 | 3692 | 0.6763 | 0.8333 |
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+ | 0.0823 | 5.0 | 4615 | 0.8609 | 0.8252 |
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+ | 0.2362 | 6.0 | 5538 | 1.1571 | 0.8163 |
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+ | 0.0242 | 7.0 | 6461 | 1.3157 | 0.8203 |
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+ | 0.0078 | 8.0 | 7384 | 1.5067 | 0.8063 |
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+ | 0.0045 | 9.0 | 8307 | 1.5694 | 0.8182 |
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+ | 0.0161 | 10.0 | 9230 | 1.6636 | 0.8168 |
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+ | 0.005 | 11.0 | 10153 | 1.7056 | 0.8185 |
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+ | 0.0057 | 12.0 | 11076 | 1.6400 | 0.8222 |
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+ | 0.0001 | 13.0 | 11999 | 1.7600 | 0.8258 |
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+ | 0.0671 | 14.0 | 12922 | 1.8091 | 0.8241 |
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+ | 0.0041 | 15.0 | 13845 | 1.8050 | 0.8225 |
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+ | 0.0 | 16.0 | 14768 | 1.8120 | 0.8222 |
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+ | 0.0556 | 17.0 | 15691 | 1.8242 | 0.8212 |
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+ | 0.0 | 18.0 | 16614 | 1.8578 | 0.8214 |
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+ | 0.0 | 19.0 | 17537 | 1.8441 | 0.8217 |
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+ | 0.0099 | 20.0 | 18460 | 1.8476 | 0.8222 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/beit-base-patch16-224-pt22k-ft22k",
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+ "architectures": [
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+ "BeitForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "auxiliary_channels": 256,
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+ "auxiliary_loss_weight": 0.4,
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+ "auxiliary_num_convs": 1,
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+ "drop_path_rate": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "HeadAbnormalities",
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+ "1": "NeckAbnormalities",
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+ "2": "Normal",
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+ "3": "TailAbnormalities"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "HeadAbnormalities": "0",
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+ "NeckAbnormalities": "1",
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+ "Normal": "2",
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+ "TailAbnormalities": "3"
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "layer_scale_init_value": 0.1,
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+ "model_type": "beit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "problem_type": "single_label_classification",
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+ "semantic_loss_ignore_index": 255,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.0",
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+ "use_absolute_position_embeddings": false,
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+ "use_relative_position_bias": true,
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+ "use_shared_relative_position_bias": false,
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+ "vocab_size": 8192
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+ }
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+ "image_processor_type": "BeitImageProcessor",
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