---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ServiModel
  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. -->

# ServiModel

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9224
- Accuracy: 0.5437

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9203        | 0.0120 | 3    | 1.0271          | 0.5264   |
| 0.7804        | 0.0239 | 6    | 0.9705          | 0.5287   |
| 0.8766        | 0.0359 | 9    | 0.9562          | 0.5299   |
| 0.8149        | 0.0478 | 12   | 0.9631          | 0.5345   |
| 0.8701        | 0.0598 | 15   | 0.9796          | 0.5379   |
| 0.992         | 0.0717 | 18   | 0.9764          | 0.5276   |
| 0.6035        | 0.0837 | 21   | 0.9932          | 0.5356   |
| 0.7398        | 0.0956 | 24   | 1.0167          | 0.5368   |
| 1.1153        | 0.1076 | 27   | 1.0184          | 0.5322   |
| 1.0794        | 0.1195 | 30   | 0.9807          | 0.5471   |
| 0.9069        | 0.1315 | 33   | 0.9571          | 0.5368   |
| 1.0911        | 0.1434 | 36   | 0.9478          | 0.5356   |
| 0.856         | 0.1554 | 39   | 0.9417          | 0.5276   |
| 0.7464        | 0.1673 | 42   | 0.9329          | 0.5368   |
| 1.0068        | 0.1793 | 45   | 0.9318          | 0.5402   |
| 0.8869        | 0.1912 | 48   | 0.9383          | 0.5402   |
| 1.0068        | 0.2032 | 51   | 0.9451          | 0.5517   |
| 0.9831        | 0.2151 | 54   | 0.9459          | 0.5460   |
| 1.0295        | 0.2271 | 57   | 0.9345          | 0.5356   |
| 0.6741        | 0.2390 | 60   | 0.9517          | 0.5414   |
| 0.9761        | 0.2510 | 63   | 0.9543          | 0.5448   |
| 0.7699        | 0.2629 | 66   | 0.9568          | 0.5368   |
| 0.9349        | 0.2749 | 69   | 0.9716          | 0.5287   |
| 0.8818        | 0.2869 | 72   | 0.9599          | 0.5322   |
| 0.857         | 0.2988 | 75   | 0.9496          | 0.5345   |
| 0.8135        | 0.3108 | 78   | 0.9521          | 0.5310   |
| 0.727         | 0.3227 | 81   | 0.9635          | 0.5402   |
| 0.9652        | 0.3347 | 84   | 0.9609          | 0.5414   |
| 0.7455        | 0.3466 | 87   | 0.9702          | 0.5299   |
| 0.7711        | 0.3586 | 90   | 0.9836          | 0.5230   |
| 0.7348        | 0.3705 | 93   | 1.0026          | 0.5276   |
| 0.8274        | 0.3825 | 96   | 1.0305          | 0.5368   |
| 0.9674        | 0.3944 | 99   | 1.0415          | 0.5276   |
| 1.0927        | 0.4064 | 102  | 1.0280          | 0.5253   |
| 1.1576        | 0.4183 | 105  | 0.9987          | 0.5356   |
| 0.8832        | 0.4303 | 108  | 0.9807          | 0.5322   |
| 0.5615        | 0.4422 | 111  | 0.9751          | 0.5437   |
| 1.2028        | 0.4542 | 114  | 0.9600          | 0.5391   |
| 0.8733        | 0.4661 | 117  | 0.9601          | 0.5448   |
| 0.8855        | 0.4781 | 120  | 0.9657          | 0.5391   |
| 1.0181        | 0.4900 | 123  | 0.9632          | 0.5379   |
| 0.8833        | 0.5020 | 126  | 0.9461          | 0.5379   |
| 1.0474        | 0.5139 | 129  | 0.9384          | 0.5425   |
| 1.173         | 0.5259 | 132  | 0.9260          | 0.5529   |
| 1.0996        | 0.5378 | 135  | 0.9186          | 0.5552   |
| 0.6445        | 0.5498 | 138  | 0.9149          | 0.5586   |
| 0.7965        | 0.5618 | 141  | 0.9176          | 0.5540   |
| 1.0051        | 0.5737 | 144  | 0.9213          | 0.5517   |
| 0.8613        | 0.5857 | 147  | 0.9298          | 0.5506   |
| 0.8603        | 0.5976 | 150  | 0.9345          | 0.5460   |
| 0.8247        | 0.6096 | 153  | 0.9306          | 0.5506   |
| 0.8808        | 0.6215 | 156  | 0.9269          | 0.5506   |
| 1.0487        | 0.6335 | 159  | 0.9235          | 0.5529   |
| 0.9654        | 0.6454 | 162  | 0.9236          | 0.5529   |
| 0.9228        | 0.6574 | 165  | 0.9196          | 0.5598   |
| 0.8636        | 0.6693 | 168  | 0.9153          | 0.5586   |
| 0.7859        | 0.6813 | 171  | 0.9174          | 0.5609   |
| 0.7514        | 0.6932 | 174  | 0.9177          | 0.5598   |
| 0.7972        | 0.7052 | 177  | 0.9187          | 0.5655   |
| 0.8669        | 0.7171 | 180  | 0.9277          | 0.5471   |
| 0.8085        | 0.7291 | 183  | 0.9406          | 0.5437   |
| 0.9855        | 0.7410 | 186  | 0.9494          | 0.5391   |
| 0.9821        | 0.7530 | 189  | 0.9533          | 0.5437   |
| 0.8769        | 0.7649 | 192  | 0.9556          | 0.5448   |
| 0.7997        | 0.7769 | 195  | 0.9610          | 0.5448   |
| 0.9333        | 0.7888 | 198  | 0.9580          | 0.5471   |
| 0.9406        | 0.8008 | 201  | 0.9454          | 0.5437   |
| 0.7489        | 0.8127 | 204  | 0.9389          | 0.5425   |
| 0.7847        | 0.8247 | 207  | 0.9348          | 0.5414   |
| 0.7151        | 0.8367 | 210  | 0.9297          | 0.5425   |
| 0.8573        | 0.8486 | 213  | 0.9259          | 0.5483   |
| 0.88          | 0.8606 | 216  | 0.9238          | 0.5529   |
| 0.8127        | 0.8725 | 219  | 0.9221          | 0.5506   |
| 0.7742        | 0.8845 | 222  | 0.9203          | 0.5506   |
| 1.0872        | 0.8964 | 225  | 0.9198          | 0.5471   |
| 0.6082        | 0.9084 | 228  | 0.9196          | 0.5471   |
| 0.6126        | 0.9203 | 231  | 0.9206          | 0.5471   |
| 0.8127        | 0.9323 | 234  | 0.9217          | 0.5460   |
| 0.8886        | 0.9442 | 237  | 0.9221          | 0.5448   |
| 0.9518        | 0.9562 | 240  | 0.9222          | 0.5448   |
| 0.7686        | 0.9681 | 243  | 0.9223          | 0.5460   |
| 0.7965        | 0.9801 | 246  | 0.9224          | 0.5437   |
| 0.7674        | 0.9920 | 249  | 0.9224          | 0.5437   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1