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timesheet_estimator

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update model card README.md

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@@ -13,12 +13,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6674
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- - Mse: 0.6674
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- - Rmse: 0.8169
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- - Mae: 0.5948
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- - R2: 0.3295
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- - Smape: 109.9213
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  ## Model description
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@@ -43,19 +43,38 @@ 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: 1
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mse | Rmse | Mae | R2 | Smape |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:--------:|
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- | No log | 0.46 | 300 | 0.7945 | 0.7945 | 0.8914 | 0.6404 | 0.2018 | 120.6558 |
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- | No log | 0.91 | 600 | 0.6674 | 0.6674 | 0.8169 | 0.5948 | 0.3295 | 109.9213 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.29.1
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  - Pytorch 1.13.1
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  - Datasets 2.9.0
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- - Tokenizers 0.13.0
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5383
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+ - Mse: 0.5383
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+ - Rmse: 0.7337
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+ - Mae: 0.5091
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+ - R2: 0.4827
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+ - Smape: 89.7730
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mae | Mse | R2 | Rmse | Smape |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:--------:|
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+ | No log | 0.46 | 300 | 0.7945 | 0.6404 | 0.7945 | 0.2018 | 0.8914 | 120.6558 |
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+ | No log | 0.91 | 600 | 0.6674 | 0.5948 | 0.6674 | 0.3295 | 0.8169 | 109.9213 |
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+ | No log | 1.37 | 900 | 0.6795 | 0.5998 | 0.6795 | 0.3174 | 0.8243 | 108.4883 |
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+ | 0.7094 | 1.82 | 1200 | 0.6327 | 0.5916 | 0.6327 | 0.3643 | 0.7954 | 111.5772 |
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+ | 0.7094 | 2.28 | 1500 | 0.6216 | 0.5712 | 0.6216 | 0.3755 | 0.7884 | 99.9257 |
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+ | 0.7094 | 2.73 | 1800 | 0.5770 | 0.5397 | 0.5770 | 0.4203 | 0.7596 | 100.1235 |
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+ | 0.5129 | 3.19 | 2100 | 0.5791 | 0.5391 | 0.5791 | 0.4182 | 0.7610 | 99.9525 |
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+ | 0.5129 | 3.64 | 2400 | 0.5796 | 0.5421 | 0.5796 | 0.4177 | 0.7613 | 99.3905 |
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+ | 0.5129 | 4.1 | 2700 | 0.5720 | 0.5354 | 0.5720 | 0.4254 | 0.7563 | 98.9299 |
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+ | 0.4448 | 4.55 | 3000 | 0.5801 | 0.5381 | 0.5801 | 0.4173 | 0.7616 | 96.1430 |
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+ | 0.4448 | 5.01 | 3300 | 0.5437 | 0.5185 | 0.5437 | 0.4775 | 0.7373 | 94.1203 |
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+ | 0.4448 | 5.46 | 3600 | 0.5111 | 0.4949 | 0.5111 | 0.5088 | 0.7149 | 92.1147 |
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+ | 0.4448 | 5.92 | 3900 | 0.5234 | 0.5106 | 0.5234 | 0.4970 | 0.7235 | 95.4636 |
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+ | 0.4877 | 6.37 | 4200 | 0.5478 | 0.5249 | 0.5478 | 0.4735 | 0.7402 | 94.5022 |
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+ | 0.4877 | 6.83 | 4500 | 0.5172 | 0.5172 | 0.7192 | 0.4998 | 0.5029 | 93.0563 |
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+ | 0.4877 | 7.28 | 4800 | 0.5318 | 0.5318 | 0.7293 | 0.5083 | 0.4889 | 90.5273 |
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+ | 0.3889 | 7.74 | 5100 | 0.5845 | 0.5845 | 0.7645 | 0.5377 | 0.4383 | 93.8608 |
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+ | 0.3889 | 8.19 | 5400 | 0.5315 | 0.5315 | 0.7291 | 0.5014 | 0.4892 | 90.2302 |
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+ | 0.3889 | 8.65 | 5700 | 0.5356 | 0.5356 | 0.7319 | 0.5010 | 0.4852 | 88.9946 |
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+ | 0.324 | 9.1 | 6000 | 0.5345 | 0.5345 | 0.7311 | 0.5028 | 0.4864 | 89.7148 |
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+ | 0.324 | 9.56 | 6300 | 0.5383 | 0.5383 | 0.7337 | 0.5091 | 0.4827 | 89.7730 |
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  ### Framework versions
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+ - Transformers 4.27.0.dev0
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  - Pytorch 1.13.1
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  - Datasets 2.9.0
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+ - Tokenizers 0.13.2