Model save
Browse files- README.md +11 -11
- config.json +9 -11
- model.safetensors +2 -2
- runs/Mar18_03-56-25_8e515caeb417/events.out.tfevents.1710734191.8e515caeb417.2485.0 +3 -0
- training_args.bin +2 -2
README.md
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name: imagefolder
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type: imagefolder
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config: default
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split:
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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.
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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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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.
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- train_batch_size: 16
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- eval_batch_size: 8
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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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- num_epochs:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.
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### Framework versions
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- Transformers 4.
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- Pytorch 2.1
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- Datasets 2.
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- Tokenizers 0.15.
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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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: 0.8907407407407407
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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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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4002
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- Accuracy: 0.8907
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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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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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.0841 | 3.7 | 1000 | 0.4002 | 0.8907 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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"2": "country",
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"3": "disco",
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"4": "hiphop",
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"5": "
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"6": "
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"7": "
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"8": "
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"9": "rock"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"country": "2",
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"disco": "3",
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"hiphop": "4",
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"
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"
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"
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"
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"rock": "9"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.
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}
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"2": "country",
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"3": "disco",
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"4": "hiphop",
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"5": "metal",
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"6": "pop",
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"7": "reggae",
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"8": "rock"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"country": "2",
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"disco": "3",
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"hiphop": "4",
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"metal": "5",
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"pop": "6",
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"reggae": "7",
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"rock": "8"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.38.2"
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}
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model.safetensors
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runs/Mar18_03-56-25_8e515caeb417/events.out.tfevents.1710734191.8e515caeb417.2485.0
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training_args.bin
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