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google_electra-small-discriminator

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End of training

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  1. README.md +20 -15
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,19 +18,19 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4973
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- - Accuracy: 0.8541
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- - F1 Macro: 0.3638
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- - Precision Destination: 0.9241
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- - Recall Destination: 0.9262
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- - Precision Origin: 0.4247
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- - Recall Origin: 0.7045
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  - Precision Other: 0.0
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  - Recall Other: 0.0
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  - Precision Transit: 0.0
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  - Recall Transit: 0.0
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- - Super Metric: 1.6307
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- - Raw Super Metric: 1.6307
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  ## Model description
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@@ -55,18 +55,23 @@ 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: 5
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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 | Accuracy | F1 Macro | Precision Destination | Recall Destination | Precision Origin | Recall Origin | Precision Other | Recall Other | Precision Transit | Recall Transit | Super Metric | Raw Super Metric |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------------:|:------------------:|:----------------:|:-------------:|:---------------:|:------------:|:-----------------:|:--------------:|:------------:|:----------------:|
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- | 0.985 | 1.0 | 185 | 0.8616 | 0.8580 | 0.2309 | 0.8580 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.98 | 1.0 |
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- | 0.7538 | 2.0 | 370 | 0.6105 | 0.8234 | 0.3503 | 0.9292 | 0.8814 | 0.3608 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.6769 | 1.6769 |
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- | 0.5364 | 3.0 | 555 | 0.5184 | 0.8503 | 0.3683 | 0.9315 | 0.9128 | 0.4217 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7082 | 1.7082 |
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- | 0.5256 | 4.0 | 740 | 0.4888 | 0.8522 | 0.3661 | 0.9278 | 0.9195 | 0.4231 | 0.75 | 0.0 | 0.0 | 0.0 | 0.0 | 1.6695 | 1.6695 |
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- | 0.522 | 5.0 | 925 | 0.4973 | 0.8541 | 0.3638 | 0.9241 | 0.9262 | 0.4247 | 0.7045 | 0.0 | 0.0 | 0.0 | 0.0 | 1.6307 | 1.6307 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5391
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+ - Accuracy: 0.8906
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+ - F1 Macro: 0.4073
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+ - Precision Destination: 0.9266
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+ - Recall Destination: 0.9597
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+ - Precision Origin: 0.6034
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+ - Recall Origin: 0.7955
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  - Precision Other: 0.0
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  - Recall Other: 0.0
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  - Precision Transit: 0.0
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  - Recall Transit: 0.0
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+ - Super Metric: 1.7552
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+ - Raw Super Metric: 1.7552
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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: 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 | Accuracy | F1 Macro | Precision Destination | Recall Destination | Precision Origin | Recall Origin | Precision Other | Recall Other | Precision Transit | Recall Transit | Super Metric | Raw Super Metric |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------------:|:------------------:|:----------------:|:-------------:|:---------------:|:------------:|:-----------------:|:--------------:|:------------:|:----------------:|
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+ | 0.9832 | 1.0 | 185 | 0.8369 | 0.8580 | 0.2309 | 0.8580 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.98 | 1.0 |
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+ | 0.6996 | 2.0 | 370 | 0.5563 | 0.8349 | 0.3584 | 0.9281 | 0.8949 | 0.3889 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.6903 | 1.6903 |
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+ | 0.5078 | 3.0 | 555 | 0.4766 | 0.8599 | 0.3710 | 0.9305 | 0.9284 | 0.44 | 0.75 | 0.0 | 0.0 | 0.0 | 0.0 | 1.6784 | 1.6784 |
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+ | 0.4209 | 4.0 | 740 | 0.4103 | 0.8714 | 0.3847 | 0.9332 | 0.9374 | 0.4861 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7328 | 1.7328 |
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+ | 0.3891 | 5.0 | 925 | 0.4396 | 0.8810 | 0.3957 | 0.9338 | 0.9463 | 0.5294 | 0.8182 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7645 | 1.7645 |
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+ | 0.2696 | 6.0 | 1110 | 0.5042 | 0.8887 | 0.4026 | 0.9304 | 0.9575 | 0.5738 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7529 | 1.7529 |
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+ | 0.3568 | 7.0 | 1295 | 0.5009 | 0.8925 | 0.4093 | 0.9267 | 0.9620 | 0.6140 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7574 | 1.7574 |
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+ | 0.2611 | 8.0 | 1480 | 0.5011 | 0.8772 | 0.3907 | 0.9316 | 0.9441 | 0.5147 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7395 | 1.7395 |
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+ | 0.2724 | 9.0 | 1665 | 0.5354 | 0.8925 | 0.4093 | 0.9267 | 0.9620 | 0.6140 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7574 | 1.7574 |
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+ | 0.3317 | 10.0 | 1850 | 0.5391 | 0.8906 | 0.4073 | 0.9266 | 0.9597 | 0.6034 | 0.7955 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7552 | 1.7552 |
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  ### Framework versions
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