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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: sevvalkapcak/newModel2
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# 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: 0.0055
- Validation Loss: 0.6577
- Train Accuracy: 0.928
- Epoch: 70
## 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 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1
|