Commit
•
dd83fcb
1
Parent(s):
f6ecd34
Model save
Browse files- README.md +132 -0
- config.json +76 -0
- model.safetensors +3 -0
- preprocessor_config.json +36 -0
- runs/May15_15-18-05_328b1d06ae1d/events.out.tfevents.1715786412.328b1d06ae1d.34.2 +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
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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: rmsprop_VitB-p16-224-1e-4-batch_16_epoch_4_classes_24
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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: 0.9683908045977011
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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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# rmsprop_VitB-p16-224-1e-4-batch_16_epoch_4_classes_24
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1712
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- Accuracy: 0.9684
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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: 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: 4
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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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| 0.0876 | 0.07 | 100 | 0.1851 | 0.9483 |
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| 0.117 | 0.14 | 200 | 0.2321 | 0.9339 |
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| 0.0244 | 0.21 | 300 | 0.1376 | 0.9641 |
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| 0.058 | 0.28 | 400 | 0.3501 | 0.9267 |
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| 0.0159 | 0.35 | 500 | 0.2359 | 0.9425 |
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| 0.0322 | 0.42 | 600 | 0.1792 | 0.9641 |
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| 0.0245 | 0.49 | 700 | 0.2543 | 0.9483 |
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| 0.0189 | 0.56 | 800 | 0.1764 | 0.9626 |
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| 0.0528 | 0.63 | 900 | 0.2989 | 0.9497 |
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| 0.0423 | 0.7 | 1000 | 0.2146 | 0.9583 |
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| 0.0585 | 0.77 | 1100 | 0.2581 | 0.9425 |
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| 0.002 | 0.84 | 1200 | 0.1778 | 0.9641 |
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| 0.0131 | 0.91 | 1300 | 0.2760 | 0.9497 |
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| 0.0889 | 0.97 | 1400 | 0.2059 | 0.9540 |
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| 0.1212 | 1.04 | 1500 | 0.2592 | 0.9440 |
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| 0.0003 | 1.11 | 1600 | 0.1900 | 0.9655 |
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| 0.0884 | 1.18 | 1700 | 0.1622 | 0.9655 |
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| 0.0188 | 1.25 | 1800 | 0.2284 | 0.9511 |
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| 0.0002 | 1.32 | 1900 | 0.1840 | 0.9670 |
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| 0.0108 | 1.39 | 2000 | 0.2478 | 0.9598 |
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| 0.0003 | 1.46 | 2100 | 0.2207 | 0.9555 |
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| 0.0183 | 1.53 | 2200 | 0.1800 | 0.9655 |
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| 0.0119 | 1.6 | 2300 | 0.1976 | 0.9598 |
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| 0.0407 | 1.67 | 2400 | 0.2089 | 0.9655 |
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| 0.0001 | 1.74 | 2500 | 0.2273 | 0.9612 |
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| 0.0005 | 1.81 | 2600 | 0.2895 | 0.9526 |
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| 0.0048 | 1.88 | 2700 | 0.2115 | 0.9569 |
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| 0.0391 | 1.95 | 2800 | 0.2026 | 0.9655 |
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| 0.0001 | 2.02 | 2900 | 0.2276 | 0.9626 |
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| 0.0108 | 2.09 | 3000 | 0.2089 | 0.9612 |
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| 0.0 | 2.16 | 3100 | 0.2548 | 0.9583 |
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| 0.0002 | 2.23 | 3200 | 0.2763 | 0.9626 |
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| 0.0002 | 2.3 | 3300 | 0.1982 | 0.9655 |
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| 0.0094 | 2.37 | 3400 | 0.2170 | 0.9655 |
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| 0.0162 | 2.44 | 3500 | 0.1912 | 0.9655 |
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| 0.0004 | 2.51 | 3600 | 0.2224 | 0.9655 |
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| 0.0029 | 2.58 | 3700 | 0.1788 | 0.9713 |
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| 0.0 | 2.65 | 3800 | 0.1954 | 0.9655 |
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| 0.0107 | 2.72 | 3900 | 0.2269 | 0.9598 |
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| 0.0001 | 2.79 | 4000 | 0.1996 | 0.9655 |
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| 0.0001 | 2.86 | 4100 | 0.2232 | 0.9626 |
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| 0.0 | 2.92 | 4200 | 0.1967 | 0.9713 |
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| 0.0003 | 2.99 | 4300 | 0.1802 | 0.9655 |
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| 0.0 | 3.06 | 4400 | 0.1779 | 0.9670 |
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| 0.0 | 3.13 | 4500 | 0.1848 | 0.9655 |
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| 0.0 | 3.2 | 4600 | 0.1849 | 0.9655 |
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| 0.0 | 3.27 | 4700 | 0.1924 | 0.9641 |
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| 0.0 | 3.34 | 4800 | 0.1802 | 0.9655 |
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| 0.0 | 3.41 | 4900 | 0.1716 | 0.9698 |
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| 0.0001 | 3.48 | 5000 | 0.1939 | 0.9670 |
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| 0.0 | 3.55 | 5100 | 0.1850 | 0.9670 |
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| 0.0 | 3.62 | 5200 | 0.1906 | 0.9684 |
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| 0.0 | 3.69 | 5300 | 0.1909 | 0.9698 |
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| 0.0 | 3.76 | 5400 | 0.1763 | 0.9698 |
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| 0.0 | 3.83 | 5500 | 0.1718 | 0.9684 |
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| 0.0 | 3.9 | 5600 | 0.1709 | 0.9684 |
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| 0.0 | 3.97 | 5700 | 0.1712 | 0.9684 |
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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",
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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": "Bhapa Pitha(\u09ad\u09be\u09aa\u09be \u09aa\u09bf\u09a0\u09be)",
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"1": "Biriyani(\u09ac\u09bf\u09b0\u09bf\u09df\u09be\u09a8\u09bf)",
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"10": "Khichuri(\u0996\u09bf\u099a\u09c1\u09a1\u09bc\u09bf)",
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15 |
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"11": "Malpua Pitha(\u09ae\u09be\u09b2\u09aa\u09c1\u09df\u09be \u09aa\u09bf\u09a0\u09be)",
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16 |
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"12": "Mustard Hilsa(\u09b8\u09b0\u09b7\u09c7 \u0987\u09b2\u09bf\u09b6)",
|
17 |
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"13": "Nakshi Pitha(\u09a8\u0995\u09b6\u09bf \u09aa\u09bf\u09a0\u09be)",
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18 |
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"14": "Panta Ilish(\u09aa\u09be\u09a8\u09cd\u09a4\u09be \u0987\u09b2\u09bf\u09b6)",
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19 |
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"15": "Patishapta Pitha(\u09aa\u09be\u099f\u09bf\u09b8\u09be\u09aa\u099f\u09be)",
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20 |
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"16": "Prawn Malai Curry(\u099a\u09bf\u0982\u09dc\u09bf \u09ae\u09be\u09b2\u09be\u0987\u0995\u09be\u09b0\u09c0)",
|
21 |
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"17": "Rasgulla(\u09b0\u09b8\u0997\u09cb\u09b2\u09cd\u09b2\u09be)",
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22 |
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"18": "Rose Cookies(\u09ab\u09c1\u09b2\u099d\u09c1\u09b0\u09bf \u09aa\u09bf\u09a0\u09be)",
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23 |
+
"19": "Roshmalai(\u09b0\u09b8\u09ae\u09be\u09b2\u09be\u0987)",
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24 |
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"2": "Chicken Pulao(\u09ae\u09cb\u09b0\u0997 \u09aa\u09cb\u09b2\u09be\u0993)",
|
25 |
+
"20": "Shahi Tukra(\u09b6\u09be\u09b9\u09bf \u099f\u09c1\u0995\u09b0\u09be)",
|
26 |
+
"21": "Shingara(\u09b8\u09bf\u0999\u09cd\u0997\u09be\u09b0\u09be)",
|
27 |
+
"22": "Sweet Yogurt(\u09ae\u09bf\u09b7\u09cd\u099f\u09bf \u09a6\u0987)",
|
28 |
+
"23": "Tehari(\u09a4\u09c7\u09b9\u09be\u09b0\u09bf)",
|
29 |
+
"3": "Chickpease Bhuna(\u099b\u09cb\u09b2\u09be\u09ad\u09c1\u09a8\u09be)",
|
30 |
+
"4": "Egg Curry(\u09a1\u09bf\u09ae\u09ad\u09c1\u09a8\u09be)",
|
31 |
+
"5": "Falooda(\u09ab\u09be\u09b2\u09c1\u09a6\u09be)",
|
32 |
+
"6": "Fuchka(\u09ab\u09c1\u099a\u0995\u09be)",
|
33 |
+
"7": "Haleem(\u09b9\u09be\u09b2\u09bf\u09ae)",
|
34 |
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"8": "Jalebi(\u099c\u09bf\u09b2\u09be\u09aa\u09c0)",
|
35 |
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"9": "Kala Bhuna(\u0995\u09be\u09b2\u09be \u09ad\u09c1\u09a8\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,
|
40 |
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"label2id": {
|
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"Bhapa Pitha(\u09ad\u09be\u09aa\u09be \u09aa\u09bf\u09a0\u09be)": "0",
|
42 |
+
"Biriyani(\u09ac\u09bf\u09b0\u09bf\u09df\u09be\u09a8\u09bf)": "1",
|
43 |
+
"Chicken Pulao(\u09ae\u09cb\u09b0\u0997 \u09aa\u09cb\u09b2\u09be\u0993)": "2",
|
44 |
+
"Chickpease Bhuna(\u099b\u09cb\u09b2\u09be\u09ad\u09c1\u09a8\u09be)": "3",
|
45 |
+
"Egg Curry(\u09a1\u09bf\u09ae\u09ad\u09c1\u09a8\u09be)": "4",
|
46 |
+
"Falooda(\u09ab\u09be\u09b2\u09c1\u09a6\u09be)": "5",
|
47 |
+
"Fuchka(\u09ab\u09c1\u099a\u0995\u09be)": "6",
|
48 |
+
"Haleem(\u09b9\u09be\u09b2\u09bf\u09ae)": "7",
|
49 |
+
"Jalebi(\u099c\u09bf\u09b2\u09be\u09aa\u09c0)": "8",
|
50 |
+
"Kala Bhuna(\u0995\u09be\u09b2\u09be \u09ad\u09c1\u09a8\u09be)": "9",
|
51 |
+
"Khichuri(\u0996\u09bf\u099a\u09c1\u09a1\u09bc\u09bf)": "10",
|
52 |
+
"Malpua Pitha(\u09ae\u09be\u09b2\u09aa\u09c1\u09df\u09be \u09aa\u09bf\u09a0\u09be)": "11",
|
53 |
+
"Mustard Hilsa(\u09b8\u09b0\u09b7\u09c7 \u0987\u09b2\u09bf\u09b6)": "12",
|
54 |
+
"Nakshi Pitha(\u09a8\u0995\u09b6\u09bf \u09aa\u09bf\u09a0\u09be)": "13",
|
55 |
+
"Panta Ilish(\u09aa\u09be\u09a8\u09cd\u09a4\u09be \u0987\u09b2\u09bf\u09b6)": "14",
|
56 |
+
"Patishapta Pitha(\u09aa\u09be\u099f\u09bf\u09b8\u09be\u09aa\u099f\u09be)": "15",
|
57 |
+
"Prawn Malai Curry(\u099a\u09bf\u0982\u09dc\u09bf \u09ae\u09be\u09b2\u09be\u0987\u0995\u09be\u09b0\u09c0)": "16",
|
58 |
+
"Rasgulla(\u09b0\u09b8\u0997\u09cb\u09b2\u09cd\u09b2\u09be)": "17",
|
59 |
+
"Rose Cookies(\u09ab\u09c1\u09b2\u099d\u09c1\u09b0\u09bf \u09aa\u09bf\u09a0\u09be)": "18",
|
60 |
+
"Roshmalai(\u09b0\u09b8\u09ae\u09be\u09b2\u09be\u0987)": "19",
|
61 |
+
"Shahi Tukra(\u09b6\u09be\u09b9\u09bf \u099f\u09c1\u0995\u09b0\u09be)": "20",
|
62 |
+
"Shingara(\u09b8\u09bf\u0999\u09cd\u0997\u09be\u09b0\u09be)": "21",
|
63 |
+
"Sweet Yogurt(\u09ae\u09bf\u09b7\u09cd\u099f\u09bf \u09a6\u0987)": "22",
|
64 |
+
"Tehari(\u09a4\u09c7\u09b9\u09be\u09b0\u09bf)": "23"
|
65 |
+
},
|
66 |
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"layer_norm_eps": 1e-12,
|
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"model_type": "vit",
|
68 |
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"num_attention_heads": 12,
|
69 |
+
"num_channels": 3,
|
70 |
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"num_hidden_layers": 12,
|
71 |
+
"patch_size": 16,
|
72 |
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"problem_type": "single_label_classification",
|
73 |
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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 sha256:51ebb3c501fae1710fba7e4f63869c8435377c783da398786e91ee2f5501c177
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size 343291648
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preprocessor_config.json
ADDED
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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/May15_15-18-05_328b1d06ae1d/events.out.tfevents.1715786412.328b1d06ae1d.34.2
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:8695e7997a10dddfa89e8dde62e26fe2f385fc601590dacc6108678e3182337e
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size 148183
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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+
version https://git-lfs.github.com/spec/v1
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+
oid sha256:6a27b26af76b37e84e02aa0ab2c212af475231a024696240825b42f5b52e26b8
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3 |
+
size 5048
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