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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: hkayesh/twitter-disaster-nlp
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. -->
# hkayesh/twitter-disaster-nlp
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: 0.2529
- Train Accuracy: 0.9074
- Validation Loss: 0.4153
- Validation Accuracy: 0.8425
- Epoch: 2
## 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1284, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.4349 | 0.8150 | 0.3635 | 0.8635 | 0 |
| 0.3233 | 0.8716 | 0.3878 | 0.8360 | 1 |
| 0.2529 | 0.9074 | 0.4153 | 0.8425 | 2 |
### Framework versions
- Transformers 4.17.0
- TensorFlow 2.6.3
- Datasets 2.1.0
- Tokenizers 0.11.6
|