rotated_maps
Browse files- README.md +79 -0
- all_results.json +13 -0
- config.json +42 -0
- eval_results.json +8 -0
- model.safetensors +3 -0
- preprocessor_config.json +22 -0
- runs/Oct31_15-36-40_e244556ed756/events.out.tfevents.1730389003.e244556ed756.183.6 +3 -0
- runs/Oct31_15-36-40_e244556ed756/events.out.tfevents.1730389108.e244556ed756.183.7 +3 -0
- train_results.json +8 -0
- trainer_state.json +242 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- image-classification
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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: vit-base-patch16-224-in21k-rotated-dungeons-v8
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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: rotated_maps
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type: imagefolder
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config: default
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split: validation
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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: 0.875
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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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# vit-base-patch16-224-in21k-rotated-dungeons-v8
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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 rotated_maps dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8643
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- Accuracy: 0.875
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 4
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- eval_batch_size: 8
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- seed: 1024
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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: 22
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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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| 0.1574 | 8.3333 | 100 | 0.8765 | 0.875 |
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| 0.1364 | 16.6667 | 200 | 0.8643 | 0.875 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.5.0+cu121
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- Datasets 3.1.0
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- Tokenizers 0.19.1
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all_results.json
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{
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"epoch": 22.0,
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"eval_accuracy": 0.875,
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"eval_loss": 0.864288330078125,
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"eval_runtime": 0.133,
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"eval_samples_per_second": 60.169,
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"eval_steps_per_second": 7.521,
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"total_flos": 8.013030801360077e+16,
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"train_loss": 0.16366353608442075,
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"train_runtime": 97.5562,
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"train_samples_per_second": 10.599,
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"train_steps_per_second": 2.706
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}
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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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": "five",
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"1": "four",
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"2": "one",
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"3": "three",
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"4": "twelve",
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"5": "two",
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"6": "zero"
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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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"five": "0",
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"four": "1",
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"one": "2",
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"three": "3",
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"twelve": "4",
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"two": "5",
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"zero": "6"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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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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"patch_size": 16,
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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": "4.44.2"
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}
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eval_results.json
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{
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"epoch": 22.0,
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"eval_accuracy": 0.875,
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"eval_loss": 0.864288330078125,
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"eval_runtime": 0.133,
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"eval_samples_per_second": 60.169,
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"eval_steps_per_second": 7.521
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6e20e702b54aeeed692141acb24f7a99c058ad4ce6328b401110a8e2f9237b79
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size 343239356
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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"size": {
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runs/Oct31_15-36-40_e244556ed756/events.out.tfevents.1730389003.e244556ed756.183.6
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version https://git-lfs.github.com/spec/v1
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size 11676
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runs/Oct31_15-36-40_e244556ed756/events.out.tfevents.1730389108.e244556ed756.183.7
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version https://git-lfs.github.com/spec/v1
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train_results.json
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trainer_state.json
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