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TheLitttleThings
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clip-archdaily-5k

Zero-Shot Image Classification
Transformers
PyTorch
clip
Generated from Trainer
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update model card README.md

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  1. README.md +31 -13
README.md CHANGED
@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3203
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  ## Model description
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@@ -39,23 +39,41 @@ The following hyperparameters were used during training:
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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_steps: 100
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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 3.001 | 0.17 | 100 | 2.9747 |
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- | 2.531 | 0.34 | 200 | 2.5566 |
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- | 2.3043 | 0.51 | 300 | 2.2206 |
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- | 1.9508 | 0.68 | 400 | 1.9649 |
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- | 1.833 | 0.85 | 500 | 1.8703 |
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- | 1.5009 | 1.02 | 600 | 1.6952 |
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- | 1.529 | 1.19 | 700 | 1.6495 |
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- | 1.2931 | 1.36 | 800 | 1.5316 |
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- | 1.3364 | 1.53 | 900 | 1.4575 |
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- | 1.2891 | 1.7 | 1000 | 1.3614 |
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- | 1.1423 | 1.87 | 1100 | 1.3203 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5681
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  ## Model description
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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_steps: 100
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.533 | 0.34 | 200 | 2.4607 |
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+ | 2.1012 | 0.68 | 400 | 1.9922 |
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+ | 1.6059 | 1.02 | 600 | 1.7986 |
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+ | 1.4557 | 1.36 | 800 | 1.6130 |
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+ | 1.4268 | 1.7 | 1000 | 1.4073 |
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+ | 0.8588 | 2.04 | 1200 | 1.2657 |
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+ | 0.8191 | 2.38 | 1400 | 1.1214 |
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+ | 0.81 | 2.72 | 1600 | 1.0418 |
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+ | 0.5546 | 3.06 | 1800 | 0.9735 |
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+ | 0.4905 | 3.4 | 2000 | 0.9006 |
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+ | 0.5209 | 3.74 | 2200 | 0.8762 |
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+ | 0.3127 | 4.08 | 2400 | 0.8457 |
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+ | 0.3145 | 4.42 | 2600 | 0.7886 |
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+ | 0.3265 | 4.76 | 2800 | 0.7853 |
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+ | 0.2215 | 5.1 | 3000 | 0.7309 |
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+ | 0.2351 | 5.44 | 3200 | 0.7082 |
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+ | 0.2332 | 5.78 | 3400 | 0.6770 |
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+ | 0.1793 | 6.12 | 3600 | 0.6856 |
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+ | 0.1617 | 6.46 | 3800 | 0.6470 |
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+ | 0.1468 | 6.8 | 4000 | 0.6700 |
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+ | 0.1293 | 7.14 | 4200 | 0.6460 |
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+ | 0.1257 | 7.48 | 4400 | 0.6415 |
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+ | 0.0975 | 7.82 | 4600 | 0.6454 |
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+ | 0.0835 | 8.16 | 4800 | 0.6111 |
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+ | 0.0856 | 8.5 | 5000 | 0.6124 |
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+ | 0.0887 | 8.84 | 5200 | 0.5956 |
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+ | 0.069 | 9.18 | 5400 | 0.5877 |
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+ | 0.0625 | 9.52 | 5600 | 0.5798 |
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+ | 0.0599 | 9.86 | 5800 | 0.5681 |
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  ### Framework versions