---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: sevvalkapcak/newModel
  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/newModel

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: 0.0146
- Validation Loss: 0.7180
- Train Accuracy: 0.909
- Epoch: 37

## 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.0133     | 0.6573          | 0.901          | 0     |
| 0.0135     | 0.7314          | 0.9065         | 1     |
| 0.0104     | 0.6544          | 0.913          | 2     |
| 0.0148     | 0.7763          | 0.9035         | 3     |
| 0.0171     | 0.7110          | 0.9055         | 4     |
| 0.0121     | 0.7075          | 0.9015         | 5     |
| 0.0126     | 0.7461          | 0.8945         | 6     |
| 0.0212     | 0.7539          | 0.9035         | 7     |
| 0.0183     | 0.7842          | 0.9005         | 8     |
| 0.0192     | 0.7431          | 0.901          | 9     |
| 0.0224     | 0.6014          | 0.9065         | 10    |
| 0.0168     | 0.6000          | 0.914          | 11    |
| 0.0133     | 0.6241          | 0.9125         | 12    |
| 0.0097     | 0.6747          | 0.9075         | 13    |
| 0.0122     | 0.7352          | 0.908          | 14    |
| 0.0123     | 0.8061          | 0.905          | 15    |
| 0.0139     | 0.7254          | 0.8985         | 16    |
| 0.0120     | 0.6856          | 0.903          | 17    |
| 0.0175     | 0.6727          | 0.905          | 18    |
| 0.0155     | 0.6912          | 0.9055         | 19    |
| 0.0192     | 0.7535          | 0.903          | 20    |
| 0.0206     | 0.7428          | 0.8995         | 21    |
| 0.0108     | 0.7883          | 0.8965         | 22    |
| 0.0159     | 0.7443          | 0.8885         | 23    |
| 0.0238     | 0.7381          | 0.8935         | 24    |
| 0.0167     | 0.7888          | 0.901          | 25    |
| 0.0207     | 0.7062          | 0.899          | 26    |
| 0.0148     | 0.7670          | 0.9065         | 27    |
| 0.0177     | 0.6694          | 0.8925         | 28    |
| 0.0157     | 0.7312          | 0.9045         | 29    |
| 0.0145     | 0.6551          | 0.905          | 30    |
| 0.0188     | 0.7582          | 0.906          | 31    |
| 0.0136     | 0.7531          | 0.9085         | 32    |
| 0.0119     | 0.7965          | 0.8905         | 33    |
| 0.0069     | 0.8430          | 0.901          | 34    |
| 0.0100     | 0.7795          | 0.8975         | 35    |
| 0.0100     | 0.9567          | 0.889          | 36    |
| 0.0146     | 0.7180          | 0.909          | 37    |


### Framework versions

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