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---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: cancerfarore/roberta-base-CancerFarore-Modela
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. -->
# cancerfarore/roberta-base-CancerFarore-Modela
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.4490
- Train End Logits Accuracy: 0.5839
- Train Start Logits Accuracy: 0.5620
- Validation Loss: 0.9562
- Validation End Logits Accuracy: 0.7038
- Validation Start Logits Accuracy: 0.7057
- Epoch: 0
## 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': 7588, '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 | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.4490 | 0.5839 | 0.5620 | 0.9562 | 0.7038 | 0.7057 | 0 |
### Framework versions
- Transformers 4.40.1
- TensorFlow 2.15.0
- Datasets 2.19.0
- Tokenizers 0.19.1
|