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detr-t5-medical-captioning

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  1. README.md +5 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2843
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- - Rougel: 0.1179
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  ## Model description
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@@ -42,23 +42,15 @@ The following hyperparameters were used during training:
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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 | Rougel |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 1.0915 | 1.0 | 236 | 1.0522 | 0.1784 |
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- | 0.6349 | 2.0 | 472 | 0.5972 | 0.1179 |
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- | 0.5186 | 3.0 | 708 | 0.4307 | 0.1179 |
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- | 0.5036 | 4.0 | 944 | 0.3281 | 0.4648 |
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- | 0.4559 | 5.0 | 1180 | 0.3233 | 0.1179 |
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- | 0.3973 | 6.0 | 1416 | 0.3013 | 0.3958 |
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- | 0.4032 | 7.0 | 1652 | 0.2943 | 0.1179 |
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- | 0.3626 | 8.0 | 1888 | 0.2892 | 0.1179 |
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- | 0.3783 | 9.0 | 2124 | 0.2878 | 0.1179 |
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- | 0.413 | 10.0 | 2360 | 0.2843 | 0.1179 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9834
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+ - Rougel: 0.1565
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  ## Model description
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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: 2
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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 | Rougel |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 1.3246 | 1.0 | 236 | 1.2553 | 0.1565 |
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+ | 0.9549 | 2.0 | 472 | 0.9834 | 0.1565 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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