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---
tags:
- generated_from_trainer
model-index:
- name: timesheet_estimator
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# timesheet_estimator
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5383
- Mse: 0.5383
- Rmse: 0.7337
- Mae: 0.5091
- R2: 0.4827
- Smape: 89.7730
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mae | Mse | R2 | Rmse | Smape |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:--------:|
| No log | 0.46 | 300 | 0.7945 | 0.6404 | 0.7945 | 0.2018 | 0.8914 | 120.6558 |
| No log | 0.91 | 600 | 0.6674 | 0.5948 | 0.6674 | 0.3295 | 0.8169 | 109.9213 |
| No log | 1.37 | 900 | 0.6795 | 0.5998 | 0.6795 | 0.3174 | 0.8243 | 108.4883 |
| 0.7094 | 1.82 | 1200 | 0.6327 | 0.5916 | 0.6327 | 0.3643 | 0.7954 | 111.5772 |
| 0.7094 | 2.28 | 1500 | 0.6216 | 0.5712 | 0.6216 | 0.3755 | 0.7884 | 99.9257 |
| 0.7094 | 2.73 | 1800 | 0.5770 | 0.5397 | 0.5770 | 0.4203 | 0.7596 | 100.1235 |
| 0.5129 | 3.19 | 2100 | 0.5791 | 0.5391 | 0.5791 | 0.4182 | 0.7610 | 99.9525 |
| 0.5129 | 3.64 | 2400 | 0.5796 | 0.5421 | 0.5796 | 0.4177 | 0.7613 | 99.3905 |
| 0.5129 | 4.1 | 2700 | 0.5720 | 0.5354 | 0.5720 | 0.4254 | 0.7563 | 98.9299 |
| 0.4448 | 4.55 | 3000 | 0.5801 | 0.5381 | 0.5801 | 0.4173 | 0.7616 | 96.1430 |
| 0.4448 | 5.01 | 3300 | 0.5437 | 0.5185 | 0.5437 | 0.4775 | 0.7373 | 94.1203 |
| 0.4448 | 5.46 | 3600 | 0.5111 | 0.4949 | 0.5111 | 0.5088 | 0.7149 | 92.1147 |
| 0.4448 | 5.92 | 3900 | 0.5234 | 0.5106 | 0.5234 | 0.4970 | 0.7235 | 95.4636 |
| 0.4877 | 6.37 | 4200 | 0.5478 | 0.5249 | 0.5478 | 0.4735 | 0.7402 | 94.5022 |
| 0.4877 | 6.83 | 4500 | 0.5172 | 0.5172 | 0.7192 | 0.4998 | 0.5029 | 93.0563 |
| 0.4877 | 7.28 | 4800 | 0.5318 | 0.5318 | 0.7293 | 0.5083 | 0.4889 | 90.5273 |
| 0.3889 | 7.74 | 5100 | 0.5845 | 0.5845 | 0.7645 | 0.5377 | 0.4383 | 93.8608 |
| 0.3889 | 8.19 | 5400 | 0.5315 | 0.5315 | 0.7291 | 0.5014 | 0.4892 | 90.2302 |
| 0.3889 | 8.65 | 5700 | 0.5356 | 0.5356 | 0.7319 | 0.5010 | 0.4852 | 88.9946 |
| 0.324 | 9.1 | 6000 | 0.5345 | 0.5345 | 0.7311 | 0.5028 | 0.4864 | 89.7148 |
| 0.324 | 9.56 | 6300 | 0.5383 | 0.5383 | 0.7337 | 0.5091 | 0.4827 | 89.7730 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2
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