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End of training

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  1. README.md +23 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9653
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  ## Model description
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@@ -35,30 +35,40 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 200
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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 |
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  |:-------------:|:-----:|:-----:|:---------------:|
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- | 1.3927 | 1.0 | 1000 | 1.3042 |
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- | 1.2589 | 2.0 | 2000 | 1.1766 |
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- | 1.236 | 3.0 | 3000 | 1.1331 |
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- | 1.0805 | 4.0 | 4000 | 1.0722 |
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- | 1.1195 | 5.0 | 5000 | 1.0177 |
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- | 1.0664 | 6.0 | 6000 | 0.9897 |
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- | 1.0407 | 7.0 | 7000 | 0.9765 |
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- | 0.9804 | 8.0 | 8000 | 0.9538 |
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- | 0.9385 | 9.0 | 9000 | 0.9482 |
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- | 0.974 | 10.0 | 10000 | 0.9492 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 6.3818
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 200
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+ - num_epochs: 20
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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 |
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  |:-------------:|:-----:|:-----:|:---------------:|
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+ | 3.9549 | 1.0 | 500 | 8.6487 |
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+ | 3.7386 | 2.0 | 1000 | 6.6653 |
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+ | 3.2303 | 3.0 | 1500 | 6.5420 |
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+ | 3.0704 | 4.0 | 2000 | 6.6156 |
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+ | 3.0275 | 5.0 | 2500 | 6.9053 |
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+ | 3.0644 | 6.0 | 3000 | 6.4292 |
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+ | 2.9575 | 7.0 | 3500 | 6.4167 |
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+ | 3.0707 | 8.0 | 4000 | 7.0283 |
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+ | 2.8764 | 9.0 | 4500 | 6.4162 |
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+ | 2.9142 | 10.0 | 5000 | 6.7128 |
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+ | 2.8474 | 11.0 | 5500 | 6.7765 |
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+ | 2.9095 | 12.0 | 6000 | 6.6026 |
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+ | 2.8555 | 13.0 | 6500 | 6.6679 |
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+ | 2.8619 | 14.0 | 7000 | 6.6986 |
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+ | 2.8407 | 15.0 | 7500 | 6.6944 |
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+ | 2.8214 | 16.0 | 8000 | 6.6572 |
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+ | 2.8244 | 17.0 | 8500 | 6.6596 |
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+ | 2.8092 | 18.0 | 9000 | 6.6372 |
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+ | 2.8896 | 19.0 | 9500 | 6.6237 |
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+ | 2.8422 | 20.0 | 10000 | 6.6249 |
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  ### Framework versions
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