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End of training

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  1. README.md +29 -8
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -15,13 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.9490
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- - eval_rmse: 0.7208
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- - eval_runtime: 252.8414
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- - eval_samples_per_second: 7.91
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- - eval_steps_per_second: 0.989
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- - epoch: 0.01
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- - step: 13
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  ## Model description
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@@ -46,7 +41,33 @@ The following hyperparameters were used during training:
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  - seed: 42
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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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- - num_epochs: 3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8989
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+ - Rmse: 0.6693
 
 
 
 
 
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  ## Model description
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  - seed: 42
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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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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rmse |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 0.9307 | 0.5 | 500 | 0.9342 | 0.6641 |
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+ | 0.9314 | 1.0 | 1000 | 0.9196 | 0.6693 |
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+ | 0.9278 | 1.5 | 1500 | 0.9063 | 0.6693 |
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+ | 0.9329 | 2.0 | 2000 | 0.8989 | 0.6693 |
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+ | 0.9239 | 2.5 | 2500 | 0.8997 | 0.6693 |
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+ | 0.9305 | 3.0 | 3000 | 0.8996 | 0.6690 |
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+ | 0.9368 | 3.5 | 3500 | 0.9510 | 0.7134 |
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+ | 0.9692 | 4.0 | 4000 | 0.9577 | 0.7134 |
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+ | 0.9575 | 4.5 | 4500 | 0.9595 | 0.9513 |
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+ | 0.9667 | 5.0 | 5000 | 0.9534 | 0.7134 |
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+ | 0.9577 | 5.5 | 5500 | 0.9501 | 0.7134 |
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+ | 0.9645 | 6.0 | 6000 | 0.9602 | 0.7134 |
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+ | 0.9657 | 6.5 | 6500 | 0.9575 | 0.9513 |
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+ | 0.9558 | 7.0 | 7000 | 0.9509 | 0.7134 |
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+ | 0.9554 | 7.5 | 7500 | 0.9545 | 0.7134 |
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+ | 0.9607 | 8.0 | 8000 | 0.9502 | 0.7134 |
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+ | 0.9584 | 8.5 | 8500 | 0.9503 | 0.7134 |
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+ | 0.9565 | 9.0 | 9000 | 0.9517 | 0.7134 |
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+ | 0.9514 | 9.5 | 9500 | 0.9522 | 0.7134 |
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+ | 0.9592 | 10.0 | 10000 | 0.9511 | 0.7134 |
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+
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  ### Framework versions
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