---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: cancerfarore/roberta-base-CancerFarore-Model
  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-Model

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: 0.5226
- Train End Logits Accuracy: 0.8429
- Train Start Logits Accuracy: 0.8179
- Validation Loss: 0.8662
- Validation End Logits Accuracy: 0.7675
- Validation Start Logits Accuracy: 0.7540
- 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': 32952, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.0834     | 0.6813                    | 0.6618                      | 0.8721          | 0.7369                         | 0.7251                           | 0     |
| 0.7019     | 0.7919                    | 0.7665                      | 0.8038          | 0.7645                         | 0.7510                           | 1     |
| 0.5226     | 0.8429                    | 0.8179                      | 0.8662          | 0.7675                         | 0.7540                           | 2     |


### Framework versions

- Transformers 4.40.1
- TensorFlow 2.15.0
- Datasets 2.19.0
- Tokenizers 0.19.1