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LiLT-RE-EN

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lilt
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LiLT-RE-EN

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  1. README.md +17 -27
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -21,10 +21,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nielsr/lilt-xlm-roberta-base](https://huggingface.co/nielsr/lilt-xlm-roberta-base) on the funsd_re dataset.
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  It achieves the following results on the evaluation set:
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- - Precision: 0.5
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- - Recall: 0.0049
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- - F1: 0.0098
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- - Loss: 0.0786
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  ## Model description
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@@ -50,32 +50,22 @@ 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_ratio: 0.1
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- - training_steps: 10000
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  ### Training results
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- | Training Loss | Epoch | Step | F1 | Validation Loss | Precision | Recall |
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- |:-------------:|:------:|:-----:|:------:|:---------------:|:---------:|:------:|
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- | 0.1604 | 26.32 | 500 | 0 | 0.1513 | 0 | 0 |
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- | 0.1012 | 52.63 | 1000 | 0.0098 | 0.0786 | 0.5 | 0.0049 |
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- | 0.0994 | 78.95 | 1500 | 0.3729 | 0.1901 | 0.2518 | 0.1847 |
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- | 0.0694 | 105.26 | 2000 | 0.3667 | 0.3346 | 0.3499 | 0.1926 |
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- | 0.0771 | 131.58 | 2500 | 0.3450 | 0.4370 | 0.3856 | 0.3295 |
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- | 0.0565 | 157.89 | 3000 | 0.3293 | 0.4679 | 0.3865 | 0.4137 |
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- | 0.0411 | 184.21 | 3500 | 0.3252 | 0.4593 | 0.3808 | 0.3624 |
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- | 0.0463 | 210.53 | 4000 | 0.3221 | 0.4728 | 0.3832 | 0.5089 |
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- | 0.0414 | 236.84 | 4500 | 0.3305 | 0.4790 | 0.3911 | 0.6137 |
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- | 0.036 | 263.16 | 5000 | 0.3275 | 0.4852 | 0.3910 | 0.4428 |
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- | 0.062 | 289.47 | 5500 | 0.3196 | 0.4802 | 0.3838 | 0.7425 |
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- | 0.0208 | 315.79 | 6000 | 0.3252 | 0.4778 | 0.387 | 0.4978 |
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- | 0.0245 | 342.11 | 6500 | 0.3229 | 0.4716 | 0.3833 | 0.7313 |
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- | 0.0274 | 368.42 | 7000 | 0.3275 | 0.4815 | 0.3898 | 0.5429 |
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- | 0.0232 | 394.74 | 7500 | 0.3262 | 0.4901 | 0.3917 | 0.4830 |
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- | 0.0207 | 421.05 | 8000 | 0.3162 | 0.4790 | 0.3810 | 0.5178 |
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- | 0.0346 | 447.37 | 8500 | 0.3274 | 0.4741 | 0.3873 | 0.4925 |
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- | 0.0229 | 473.68 | 9000 | 0.3219 | 0.4654 | 0.3806 | 0.5514 |
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- | 0.0253 | 500.0 | 9500 | 0.3261 | 0.4802 | 0.3884 | 0.5878 |
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- | 0.0186 | 526.32 | 10000 | 0.3202 | 0.4728 | 0.3819 | 0.5508 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [nielsr/lilt-xlm-roberta-base](https://huggingface.co/nielsr/lilt-xlm-roberta-base) on the funsd_re dataset.
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  It achieves the following results on the evaluation set:
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+ - Precision: 0.3264
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+ - Recall: 0.4864
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+ - F1: 0.3907
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+ - Loss: 0.4377
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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_ratio: 0.1
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+ - training_steps: 5000
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  ### Training results
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+ | Training Loss | Epoch | Step | F1 | Validation Loss | Precision | Recall |
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+ |:-------------:|:------:|:----:|:------:|:---------------:|:---------:|:------:|
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+ | 0.1604 | 26.32 | 500 | 0 | 0.1513 | 0 | 0 |
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+ | 0.1012 | 52.63 | 1000 | 0.0098 | 0.0786 | 0.5 | 0.0049 |
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+ | 0.0994 | 78.95 | 1500 | 0.2518 | 0.1847 | 0.3729 | 0.1901 |
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+ | 0.0694 | 105.26 | 2000 | 0.3499 | 0.1926 | 0.3667 | 0.3346 |
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+ | 0.0771 | 131.58 | 2500 | 0.3856 | 0.3295 | 0.3450 | 0.4370 |
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+ | 0.0565 | 157.89 | 3000 | 0.3865 | 0.4137 | 0.3293 | 0.4679 |
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+ | 0.0411 | 184.21 | 3500 | 0.3808 | 0.3624 | 0.3252 | 0.4593 |
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+ | 0.0463 | 210.53 | 4000 | 0.3832 | 0.5089 | 0.3221 | 0.4728 |
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+ | 0.0414 | 236.84 | 4500 | 0.3911 | 0.6137 | 0.3305 | 0.4790 |
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+ | 0.036 | 263.16 | 5000 | 0.3910 | 0.4428 | 0.3275 | 0.4852 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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