transformers tf distilbert fill-mask generated_from_keras_callback base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: tunarebus/distilbert-base-uncased-finetuned-tweetdinastipolitik
  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. -->

# tunarebus/distilbert-base-uncased-finetuned-tweetdinastipolitik

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: 2.3297
- Validation Loss: 2.3462
- Epoch: 34

## 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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -958, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.9633     | 4.7385          | 0     |
| 4.7409     | 4.4192          | 1     |
| 4.5418     | 4.2812          | 2     |
| 4.3390     | 4.1513          | 3     |
| 4.1633     | 3.9455          | 4     |
| 3.9945     | 3.7719          | 5     |
| 3.8723     | 3.6903          | 6     |
| 3.6898     | 3.5449          | 7     |
| 3.5524     | 3.3732          | 8     |
| 3.3717     | 3.1554          | 9     |
| 3.2974     | 3.1077          | 10    |
| 3.1591     | 2.9884          | 11    |
| 3.0308     | 2.9435          | 12    |
| 2.9841     | 2.8299          | 13    |
| 2.8901     | 2.7394          | 14    |
| 2.7851     | 2.6936          | 15    |
| 2.7536     | 2.6745          | 16    |
| 2.6951     | 2.5683          | 17    |
| 2.6414     | 2.5420          | 18    |
| 2.5789     | 2.5220          | 19    |
| 2.4913     | 2.4737          | 20    |
| 2.4694     | 2.4265          | 21    |
| 2.3930     | 2.3917          | 22    |
| 2.4195     | 2.4069          | 23    |
| 2.3199     | 2.3916          | 24    |
| 2.3211     | 2.3084          | 25    |
| 2.3548     | 2.3648          | 26    |
| 2.3584     | 2.4071          | 27    |
| 2.3544     | 2.3168          | 28    |
| 2.3077     | 2.4003          | 29    |
| 2.3576     | 2.3952          | 30    |
| 2.3485     | 2.3161          | 31    |
| 2.3258     | 2.3230          | 32    |
| 2.3272     | 2.3355          | 33    |
| 2.3297     | 2.3462          | 34    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
