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Melo1512
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vit-msn-small-beta-fia-manually-enhanced-HSV_test_5

Image Classification
Transformers
TensorBoard
Safetensors
vit_msn
Generated from Trainer
Eval Results
Inference Endpoints
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  2. model.safetensors +1 -1
  3. runs/Jan27_17-36-47_db1093ce036b/events.out.tfevents.1737999413.db1093ce036b.224.12 +2 -2
README.md ADDED
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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: facebook/vit-msn-small
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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: vit-msn-small-beta-fia-manually-enhanced-HSV_test_5
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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: 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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+
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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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+ # vit-msn-small-beta-fia-manually-enhanced-HSV_test_5
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+
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+ This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3460
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+ - Accuracy: 0.875
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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: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 5
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+ - total_train_batch_size: 320
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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: 0.25
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+ - num_epochs: 100
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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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+ | No log | 0.7143 | 1 | 1.1106 | 0.2292 |
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+ | No log | 1.4286 | 2 | 1.0984 | 0.2569 |
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+ | No log | 2.8571 | 4 | 1.0400 | 0.4097 |
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+ | No log | 3.5714 | 5 | 0.9960 | 0.5486 |
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+ | No log | 5.0 | 7 | 0.8868 | 0.7292 |
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+ | No log | 5.7143 | 8 | 0.8263 | 0.7778 |
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+ | No log | 6.4286 | 9 | 0.7651 | 0.8056 |
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+ | 0.9808 | 7.8571 | 11 | 0.6521 | 0.8125 |
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+ | 0.9808 | 8.5714 | 12 | 0.6052 | 0.8125 |
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+ | 0.9808 | 10.0 | 14 | 0.5388 | 0.8125 |
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+ | 0.9808 | 10.7143 | 15 | 0.5174 | 0.8125 |
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+ | 0.9808 | 11.4286 | 16 | 0.5032 | 0.8125 |
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+ | 0.9808 | 12.8571 | 18 | 0.5022 | 0.8125 |
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+ | 0.9808 | 13.5714 | 19 | 0.5044 | 0.8194 |
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+ | 0.5431 | 15.0 | 21 | 0.4773 | 0.8264 |
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+ | 0.5431 | 15.7143 | 22 | 0.4439 | 0.8333 |
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+ | 0.5431 | 16.4286 | 23 | 0.4198 | 0.8403 |
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+ | 0.5431 | 17.8571 | 25 | 0.3873 | 0.8819 |
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+ | 0.5431 | 18.5714 | 26 | 0.3730 | 0.8889 |
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+ | 0.5431 | 20.0 | 28 | 0.3774 | 0.9028 |
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+ | 0.5431 | 20.7143 | 29 | 0.3705 | 0.9097 |
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+ | 0.4028 | 21.4286 | 30 | 0.3587 | 0.9097 |
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+ | 0.4028 | 22.8571 | 32 | 0.3662 | 0.8958 |
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+ | 0.4028 | 23.5714 | 33 | 0.3779 | 0.8681 |
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+ | 0.4028 | 25.0 | 35 | 0.4322 | 0.8264 |
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+ | 0.4028 | 25.7143 | 36 | 0.3944 | 0.8333 |
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+ | 0.4028 | 26.4286 | 37 | 0.3585 | 0.8889 |
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+ | 0.4028 | 27.8571 | 39 | 0.3608 | 0.8889 |
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+ | 0.3497 | 28.5714 | 40 | 0.3972 | 0.8472 |
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+ | 0.3497 | 30.0 | 42 | 0.3805 | 0.8611 |
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+ | 0.3497 | 30.7143 | 43 | 0.3611 | 0.8819 |
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+ | 0.3497 | 31.4286 | 44 | 0.3267 | 0.9167 |
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+ | 0.3497 | 32.8571 | 46 | 0.3403 | 0.9028 |
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+ | 0.3497 | 33.5714 | 47 | 0.3751 | 0.875 |
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+ | 0.3497 | 35.0 | 49 | 0.3801 | 0.8681 |
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+ | 0.3278 | 35.7143 | 50 | 0.3499 | 0.8958 |
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+ | 0.3278 | 36.4286 | 51 | 0.3384 | 0.8958 |
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+ | 0.3278 | 37.8571 | 53 | 0.3642 | 0.8542 |
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+ | 0.3278 | 38.5714 | 54 | 0.3997 | 0.8194 |
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+ | 0.3278 | 40.0 | 56 | 0.3843 | 0.8403 |
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+ | 0.3278 | 40.7143 | 57 | 0.3676 | 0.8681 |
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+ | 0.3278 | 41.4286 | 58 | 0.3464 | 0.9028 |
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+ | 0.3334 | 42.8571 | 60 | 0.3618 | 0.8819 |
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+ | 0.3334 | 43.5714 | 61 | 0.4006 | 0.8194 |
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+ | 0.3334 | 45.0 | 63 | 0.4931 | 0.7639 |
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+ | 0.3334 | 45.7143 | 64 | 0.4845 | 0.7708 |
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+ | 0.3334 | 46.4286 | 65 | 0.4485 | 0.7917 |
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+ | 0.3334 | 47.8571 | 67 | 0.3783 | 0.8472 |
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+ | 0.3334 | 48.5714 | 68 | 0.3723 | 0.8472 |
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+ | 0.3334 | 50.0 | 70 | 0.4077 | 0.8125 |
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+ | 0.3334 | 50.7143 | 71 | 0.4381 | 0.7986 |
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+ | 0.3334 | 51.4286 | 72 | 0.4627 | 0.7847 |
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+ | 0.3334 | 52.8571 | 74 | 0.4445 | 0.7986 |
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+ | 0.3334 | 53.5714 | 75 | 0.4141 | 0.8125 |
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+ | 0.3334 | 55.0 | 77 | 0.3489 | 0.8681 |
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+ | 0.3334 | 55.7143 | 78 | 0.3371 | 0.8958 |
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+ | 0.3334 | 56.4286 | 79 | 0.3358 | 0.8889 |
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+ | 0.3105 | 57.8571 | 81 | 0.3539 | 0.8681 |
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+ | 0.3105 | 58.5714 | 82 | 0.3678 | 0.8542 |
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+ | 0.3105 | 60.0 | 84 | 0.3931 | 0.8264 |
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+ | 0.3105 | 60.7143 | 85 | 0.3938 | 0.8264 |
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+ | 0.3105 | 61.4286 | 86 | 0.3897 | 0.8472 |
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+ | 0.3105 | 62.8571 | 88 | 0.3638 | 0.8611 |
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+ | 0.3105 | 63.5714 | 89 | 0.3496 | 0.875 |
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+ | 0.3061 | 65.0 | 91 | 0.3305 | 0.8958 |
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+ | 0.3061 | 65.7143 | 92 | 0.3284 | 0.9028 |
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+ | 0.3061 | 66.4286 | 93 | 0.3284 | 0.8958 |
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+ | 0.3061 | 67.8571 | 95 | 0.3337 | 0.8958 |
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+ | 0.3061 | 68.5714 | 96 | 0.3374 | 0.8889 |
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+ | 0.3061 | 70.0 | 98 | 0.3442 | 0.875 |
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+ | 0.3061 | 70.7143 | 99 | 0.3452 | 0.875 |
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+ | 0.3137 | 71.4286 | 100 | 0.3460 | 0.875 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.19.1
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