---
tags:
- generated_from_keras_callback
model-index:
- name: distilbert_new2_0060
  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. -->

# distilbert_new2_0060

This model is a fine-tuned version of [/content/drive/MyDrive/Colab Notebooks/oscar/trybackup_distilbert/new_backup_0105105](https://huggingface.co//content/drive/MyDrive/Colab Notebooks/oscar/trybackup_distilbert/new_backup_0105105) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.9522
- Validation Loss: 0.9345
- Epoch: 59

## 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.0180     | 0.9873          | 0     |
| 1.0163     | 0.9878          | 1     |
| 1.0145     | 0.9856          | 2     |
| 1.0139     | 0.9830          | 3     |
| 1.0122     | 0.9831          | 4     |
| 1.0118     | 0.9830          | 5     |
| 1.0094     | 0.9800          | 6     |
| 1.0075     | 0.9809          | 7     |
| 1.0066     | 0.9784          | 8     |
| 1.0062     | 0.9768          | 9     |
| 1.0032     | 0.9751          | 10    |
| 1.0023     | 0.9764          | 11    |
| 1.0008     | 0.9735          | 12    |
| 0.9994     | 0.9730          | 13    |
| 0.9986     | 0.9761          | 14    |
| 0.9975     | 0.9714          | 15    |
| 0.9953     | 0.9708          | 16    |
| 0.9941     | 0.9683          | 17    |
| 0.9933     | 0.9681          | 18    |
| 0.9920     | 0.9688          | 19    |
| 0.9907     | 0.9648          | 20    |
| 0.9897     | 0.9625          | 21    |
| 0.9890     | 0.9642          | 22    |
| 0.9873     | 0.9633          | 23    |
| 0.9867     | 0.9618          | 24    |
| 0.9857     | 0.9600          | 25    |
| 0.9839     | 0.9598          | 26    |
| 0.9827     | 0.9585          | 27    |
| 0.9821     | 0.9607          | 28    |
| 0.9809     | 0.9579          | 29    |
| 0.9803     | 0.9561          | 30    |
| 0.9786     | 0.9563          | 31    |
| 0.9774     | 0.9536          | 32    |
| 0.9766     | 0.9542          | 33    |
| 0.9756     | 0.9523          | 34    |
| 0.9743     | 0.9525          | 35    |
| 0.9730     | 0.9513          | 36    |
| 0.9721     | 0.9507          | 37    |
| 0.9715     | 0.9506          | 38    |
| 0.9702     | 0.9482          | 39    |
| 0.9694     | 0.9493          | 40    |
| 0.9689     | 0.9462          | 41    |
| 0.9673     | 0.9463          | 42    |
| 0.9669     | 0.9444          | 43    |
| 0.9659     | 0.9450          | 44    |
| 0.9643     | 0.9429          | 45    |
| 0.9625     | 0.9432          | 46    |
| 0.9625     | 0.9428          | 47    |
| 0.9609     | 0.9408          | 48    |
| 0.9598     | 0.9399          | 49    |
| 0.9596     | 0.9407          | 50    |
| 0.9590     | 0.9393          | 51    |
| 0.9580     | 0.9380          | 52    |
| 0.9562     | 0.9383          | 53    |
| 0.9558     | 0.9369          | 54    |
| 0.9543     | 0.9379          | 55    |
| 0.9545     | 0.9362          | 56    |
| 0.9534     | 0.9349          | 57    |
| 0.9523     | 0.9338          | 58    |
| 0.9522     | 0.9345          | 59    |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1