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End of training

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  1. README.md +28 -9
  2. model.safetensors +1 -1
  3. training_args.bin +2 -2
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 [microsoft/table-structure-recognition-v1.1-all](https://huggingface.co/microsoft/table-structure-recognition-v1.1-all) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.9790
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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: 1e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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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: 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 |
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- |:-------------:|:------:|:----:|:---------------:|
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- | 6.5464 | 3.7037 | 100 | 6.0902 |
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- | 6.0842 | 7.4074 | 200 | 4.9790 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/table-structure-recognition-v1.1-all](https://huggingface.co/microsoft/table-structure-recognition-v1.1-all) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.2890
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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: 1e-06
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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  - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 8
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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: linear
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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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+ | 9.2523 | 1.0 | 14 | 9.3207 |
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+ | 7.9949 | 2.0 | 28 | 9.0533 |
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+ | 8.2292 | 3.0 | 42 | 8.6547 |
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+ | 7.1495 | 4.0 | 56 | 8.0844 |
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+ | 6.9055 | 5.0 | 70 | 7.3339 |
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+ | 7.0771 | 6.0 | 84 | 7.2344 |
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+ | 5.6554 | 7.0 | 98 | 6.6026 |
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+ | 5.5633 | 8.0 | 112 | 6.3610 |
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+ | 4.9506 | 9.0 | 126 | 5.9567 |
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+ | 4.0856 | 10.0 | 140 | 5.9191 |
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+ | 4.4286 | 11.0 | 154 | 5.6374 |
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+ | 2.9043 | 12.0 | 168 | 4.9525 |
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+ | 3.4755 | 13.0 | 182 | 4.6846 |
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+ | 3.4152 | 14.0 | 196 | 4.3171 |
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+ | 2.8456 | 15.0 | 210 | 3.5661 |
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+ | 2.4149 | 16.0 | 224 | 3.6150 |
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+ | 1.9328 | 17.0 | 238 | 3.2264 |
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+ | 1.8503 | 18.0 | 252 | 2.8540 |
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+ | 1.596 | 18.5981 | 260 | 2.2890 |
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  ### Framework versions
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