Model save
Browse files- README.md +106 -0
- config.json +48 -0
- model.safetensors +3 -0
- preprocessor_config.json +36 -0
- runs/Apr15_19-54-29_beac81f7e97f/events.out.tfevents.1713210973.beac81f7e97f.34.0 +3 -0
- training_args.bin +3 -0
README.md
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---
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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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- 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: Action_model
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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: 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: 0.78
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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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# Action_model
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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: 0.9408
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- Accuracy: 0.78
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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: 0.0001
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- train_batch_size: 32
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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: 10
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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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| 1.1382 | 0.32 | 100 | 1.0002 | 0.7676 |
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| 0.782 | 0.64 | 200 | 0.7673 | 0.7676 |
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| 0.6289 | 0.96 | 300 | 0.7073 | 0.7867 |
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| 0.5028 | 1.27 | 400 | 0.7261 | 0.7686 |
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| 0.4746 | 1.59 | 500 | 0.7464 | 0.7619 |
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| 0.4298 | 1.91 | 600 | 0.6551 | 0.7990 |
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| 0.3488 | 2.23 | 700 | 0.7359 | 0.7733 |
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| 0.266 | 2.55 | 800 | 0.8296 | 0.7514 |
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| 0.3651 | 2.87 | 900 | 0.8661 | 0.7305 |
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| 0.2796 | 3.18 | 1000 | 0.7188 | 0.7867 |
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| 0.2703 | 3.5 | 1100 | 0.8422 | 0.7476 |
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| 0.2608 | 3.82 | 1200 | 0.8207 | 0.7724 |
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| 0.251 | 4.14 | 1300 | 1.0252 | 0.7267 |
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| 0.2085 | 4.46 | 1400 | 1.0475 | 0.7171 |
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| 0.1715 | 4.78 | 1500 | 0.8852 | 0.7495 |
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| 0.2051 | 5.1 | 1600 | 0.8164 | 0.7790 |
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| 0.1481 | 5.41 | 1700 | 0.8825 | 0.7629 |
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| 0.177 | 5.73 | 1800 | 0.8623 | 0.7867 |
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| 0.1607 | 6.05 | 1900 | 0.9487 | 0.7610 |
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| 0.1273 | 6.37 | 2000 | 0.8985 | 0.7733 |
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| 0.1609 | 6.69 | 2100 | 0.9624 | 0.7505 |
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| 0.1583 | 7.01 | 2200 | 0.9015 | 0.7781 |
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| 0.1178 | 7.32 | 2300 | 0.9143 | 0.7762 |
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| 0.1175 | 7.64 | 2400 | 0.9671 | 0.7590 |
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| 0.1257 | 7.96 | 2500 | 0.8925 | 0.7838 |
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| 0.0939 | 8.28 | 2600 | 0.9257 | 0.7705 |
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| 0.1238 | 8.6 | 2700 | 0.9797 | 0.7648 |
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| 0.1219 | 8.92 | 2800 | 0.9399 | 0.7724 |
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| 0.0985 | 9.24 | 2900 | 0.9940 | 0.7648 |
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| 0.1069 | 9.55 | 3000 | 0.9392 | 0.7743 |
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| 0.0589 | 9.87 | 3100 | 0.9408 | 0.78 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.1.2
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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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{
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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": "\u0995\u09a5\u09be_\u09ac\u09b2\u09be",
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"1": "\u0995\u09ae\u09cd\u09aa\u09bf\u0989\u099f\u09be\u09b0_\u09ac\u09cd\u09af\u09ac\u09b9\u09be\u09b0_\u0995\u09b0\u09be",
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"2": "\u0996\u09be\u0993\u09df\u09be",
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"3": "\u0996\u09c7\u09b2\u09be_\u0995\u09b0\u09be",
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"4": "\u0998\u09c1\u09ae\u09be\u09a8\u09cb",
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"5": "\u09aa\u09be\u09a8_\u0995\u09b0\u09be",
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"6": "\u09aa\u09dc\u09be",
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"7": "\u09b0\u09be\u09a8\u09cd\u09a8\u09be_\u0995\u09b0\u09be",
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"8": "\u09b2\u09c7\u0996\u09be",
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"9": "\u09b9\u09be\u0981\u099f\u09be"
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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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"\u0995\u09a5\u09be_\u09ac\u09b2\u09be": "0",
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"\u0995\u09ae\u09cd\u09aa\u09bf\u0989\u099f\u09be\u09b0_\u09ac\u09cd\u09af\u09ac\u09b9\u09be\u09b0_\u0995\u09b0\u09be": "1",
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"\u0996\u09be\u0993\u09df\u09be": "2",
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"\u0996\u09c7\u09b2\u09be_\u0995\u09b0\u09be": "3",
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"\u0998\u09c1\u09ae\u09be\u09a8\u09cb": "4",
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"\u09aa\u09be\u09a8_\u0995\u09b0\u09be": "5",
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"\u09aa\u09dc\u09be": "6",
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"\u09b0\u09be\u09a8\u09cd\u09a8\u09be_\u0995\u09b0\u09be": "7",
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"\u09b2\u09c7\u0996\u09be": "8",
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"\u09b9\u09be\u0981\u099f\u09be": "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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"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": "4.39.3"
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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 sha256:5ff997581ddd6642e58b1bb4fe1550a4aea0cc57679090651e721750b79b12b0
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size 343248584
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preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"do_resize",
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"size",
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"resample",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"return_tensors",
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"data_format",
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"input_data_format"
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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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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTFeatureExtractor",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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runs/Apr15_19-54-29_beac81f7e97f/events.out.tfevents.1713210973.beac81f7e97f.34.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:bd7438baee405769b0c742d9a5b723ddc8ebdd18d7bcbdf38f27c74d46285eb8
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size 49066
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8894c7e4e95f3786de873c5a43602402b76fd332eea765b39d0b3d59a27cf039
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size 4920
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