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---
base_model: nlpaueb/bert-base-greek-uncased-v1
tags:
- generated_from_keras_callback
model-index:
- name: czigopis/bert-base-greek-uncased-v1-finetuned-on-OGTDv1
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. -->
# czigopis/bert-base-greek-uncased-v1-finetuned-on-OGTDv1
This model is a fine-tuned version of [nlpaueb/bert-base-greek-uncased-v1](https://huggingface.co/nlpaueb/bert-base-greek-uncased-v1) on the [Offensive Greek Tweet Dataset (OGTD)](https://zpitenis.com/ogtd).
It achieves the following results on the evaluation set:
- Train Loss: 0.1390
- Validation Loss: 0.4815
- Train Matthews Correlation: 0.6669
- Train F1: 0.8385
- Train Accuracy: 0.8333
- Epoch: 4
## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 9805, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Matthews Correlation | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------------------:|:--------:|:--------------:|:-----:|
| 0.6338 | 0.5099 | 0.5313 | 0.7560 | 0.7642 | 0 |
| 0.4309 | 0.3983 | 0.6669 | 0.8339 | 0.8333 | 1 |
| 0.3024 | 0.4196 | 0.6594 | 0.8220 | 0.8280 | 2 |
| 0.2222 | 0.4432 | 0.6666 | 0.8374 | 0.8333 | 3 |
| 0.1390 | 0.4815 | 0.6669 | 0.8385 | 0.8333 | 4 |
### Framework versions
- Transformers 4.40.2
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
|