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---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_keras_callback
model-index:
- name: Meli101/biobert-v1.1-text-classifier-tf
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. -->
# Meli101/biobert-v1.1-text-classifier-tf
This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1344
- Validation Loss: 0.2721
- Train Precision: 0.9069
- Train Recall: 0.9056
- Train Accuracy: 0.9056
- Train F1: 0.9058
- 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', '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': 2e-05, 'decay_steps': 1535, '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 Precision | Train Recall | Train Accuracy | Train F1 | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------------:|:--------:|:-----:|
| 0.5948 | 0.3185 | 0.8893 | 0.8847 | 0.8853 | 0.8858 | 0 |
| 0.2565 | 0.2451 | 0.9127 | 0.9124 | 0.9121 | 0.9121 | 1 |
| 0.1344 | 0.2721 | 0.9069 | 0.9056 | 0.9056 | 0.9058 | 2 |
### Framework versions
- Transformers 4.38.1
- TensorFlow 2.15.0
- Datasets 2.17.1
- Tokenizers 0.15.2
|