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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: tunarebus/distilbert-base-uncased-finetuned-imdb
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-imdb
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: 2.3941
- Validation Loss: 2.4019
- Epoch: 19
## 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': -949, '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 |
|:----------:|:---------------:|:-----:|
| 2.3668 | 2.3869 | 0 |
| 2.4055 | 2.3907 | 1 |
| 2.3880 | 2.3301 | 2 |
| 2.3677 | 2.4133 | 3 |
| 2.3891 | 2.4048 | 4 |
| 2.3861 | 2.4312 | 5 |
| 2.4031 | 2.3794 | 6 |
| 2.3730 | 2.3708 | 7 |
| 2.4306 | 2.3910 | 8 |
| 2.4102 | 2.3748 | 9 |
| 2.4285 | 2.4060 | 10 |
| 2.4150 | 2.4133 | 11 |
| 2.3953 | 2.4465 | 12 |
| 2.4173 | 2.3387 | 13 |
| 2.3997 | 2.3561 | 14 |
| 2.4091 | 2.4217 | 15 |
| 2.4050 | 2.3832 | 16 |
| 2.4103 | 2.4008 | 17 |
| 2.4019 | 2.3851 | 18 |
| 2.3941 | 2.4019 | 19 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0
|