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# sevvalkapcak/newModel2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0138
- Validation Loss: 0.6631
- Train Accuracy: 0.9225
- Epoch: 89

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.2465     | 0.2029          | 0.9085         | 0     |
| 0.1354     | 0.1302          | 0.939          | 1     |
| 0.1121     | 0.1588          | 0.934          | 2     |
| 0.0945     | 0.1551          | 0.937          | 3     |
| 0.0815     | 0.1696          | 0.939          | 4     |
| 0.0778     | 0.1647          | 0.932          | 5     |
| 0.0522     | 0.2356          | 0.931          | 6     |
| 0.0444     | 0.2861          | 0.9335         | 7     |
| 0.0329     | 0.2144          | 0.9355         | 8     |
| 0.0290     | 0.2548          | 0.935          | 9     |
| 0.0222     | 0.2866          | 0.93           | 10    |
| 0.0256     | 0.2787          | 0.9385         | 11    |
| 0.0267     | 0.2764          | 0.941          | 12    |
| 0.0201     | 0.2888          | 0.9315         | 13    |
| 0.0221     | 0.2737          | 0.934          | 14    |
| 0.0174     | 0.4403          | 0.93           | 15    |
| 0.0170     | 0.2836          | 0.932          | 16    |
| 0.0214     | 0.3033          | 0.9375         | 17    |
| 0.0125     | 0.3894          | 0.934          | 18    |
| 0.0271     | 0.3687          | 0.9305         | 19    |
| 0.0154     | 0.3817          | 0.9305         | 20    |
| 0.0149     | 0.4736          | 0.93           | 21    |
| 0.0196     | 0.4435          | 0.9325         | 22    |
| 0.0124     | 0.4873          | 0.929          | 23    |
| 0.0157     | 0.4008          | 0.932          | 24    |
| 0.0153     | 0.4074          | 0.931          | 25    |
| 0.0176     | 0.3996          | 0.9295         | 26    |
| 0.0160     | 0.3652          | 0.9355         | 27    |
| 0.0081     | 0.4446          | 0.934          | 28    |
| 0.0098     | 0.5249          | 0.934          | 29    |
| 0.0151     | 0.4112          | 0.937          | 30    |
| 0.0124     | 0.4888          | 0.929          | 31    |
| 0.0146     | 0.5022          | 0.9325         | 32    |
| 0.0130     | 0.5585          | 0.9305         | 33    |
| 0.0102     | 0.4304          | 0.935          | 34    |
| 0.0158     | 0.4239          | 0.933          | 35    |
| 0.0156     | 0.4849          | 0.93           | 36    |
| 0.0153     | 0.5097          | 0.9245         | 37    |
| 0.0135     | 0.4689          | 0.934          | 38    |
| 0.0178     | 0.4578          | 0.9285         | 39    |
| 0.0124     | 0.4083          | 0.9275         | 40    |
| 0.0106     | 0.4946          | 0.926          | 41    |
| 0.0098     | 0.4908          | 0.927          | 42    |
| 0.0131     | 0.5604          | 0.928          | 43    |
| 0.0143     | 0.4226          | 0.9315         | 44    |
| 0.0105     | 0.5664          | 0.9245         | 45    |
| 0.0189     | 0.5121          | 0.925          | 46    |
| 0.0148     | 0.5259          | 0.9245         | 47    |
| 0.0090     | 0.4567          | 0.9295         | 48    |
| 0.0156     | 0.4633          | 0.926          | 49    |
| 0.0128     | 0.5222          | 0.9295         | 50    |
| 0.0118     | 0.5461          | 0.921          | 51    |
| 0.0172     | 0.4626          | 0.927          | 52    |
| 0.0129     | 0.5266          | 0.922          | 53    |
| 0.0159     | 0.5203          | 0.925          | 54    |
| 0.0106     | 0.5360          | 0.9265         | 55    |
| 0.0158     | 0.4766          | 0.9305         | 56    |
| 0.0106     | 0.5630          | 0.926          | 57    |
| 0.0142     | 0.6162          | 0.922          | 58    |
| 0.0137     | 0.5518          | 0.916          | 59    |
| 0.0083     | 0.6281          | 0.9155         | 60    |
| 0.0071     | 0.6263          | 0.9245         | 61    |
| 0.0116     | 0.6166          | 0.9235         | 62    |
| 0.0162     | 0.5217          | 0.9195         | 63    |
| 0.0158     | 0.6366          | 0.9215         | 64    |
| 0.0120     | 0.5511          | 0.9245         | 65    |
| 0.0093     | 0.4895          | 0.9225         | 66    |
| 0.0094     | 0.5207          | 0.9255         | 67    |
| 0.0067     | 0.6252          | 0.9275         | 68    |
| 0.0058     | 0.6934          | 0.9235         | 69    |
| 0.0055     | 0.6577          | 0.928          | 70    |
| 0.0073     | 0.5865          | 0.9255         | 71    |
| 0.0336     | 0.4875          | 0.9175         | 72    |
| 0.0177     | 0.5256          | 0.923          | 73    |
| 0.0143     | 0.5042          | 0.917          | 74    |
| 0.0076     | 0.6803          | 0.9225         | 75    |
| 0.0114     | 0.5571          | 0.9205         | 76    |
| 0.0118     | 0.5649          | 0.9235         | 77    |
| 0.0147     | 0.5592          | 0.9245         | 78    |
| 0.0109     | 0.6044          | 0.9195         | 79    |
| 0.0095     | 0.6940          | 0.921          | 80    |
| 0.0139     | 0.6246          | 0.9245         | 81    |
| 0.0145     | 0.7057          | 0.917          | 82    |
| 0.0147     | 0.6455          | 0.9155         | 83    |
| 0.0100     | 0.6044          | 0.922          | 84    |
| 0.0074     | 0.6786          | 0.92           | 85    |
| 0.0093     | 0.7300          | 0.9125         | 86    |
| 0.0152     | 0.6264          | 0.9205         | 87    |
| 0.0115     | 0.6208          | 0.915          | 88    |
| 0.0138     | 0.6631          | 0.9225         | 89    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "sevvalkapcak/newModel2", "results": []}]}
transformers tf distilbert text-classification generated_from_keras_callback base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us