---
license: mit
base_model: vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC
tags:
- generated_from_keras_callback
model-index:
- name: vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC-FT-TyDiQA_AUQC
  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. -->

# vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC-FT-TyDiQA_AUQC

This model is a fine-tuned version of [vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC](https://huggingface.co/vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1588
- Train End Logits Accuracy: 0.9455
- Train Start Logits Accuracy: 0.9579
- Validation Loss: 0.6655
- Validation End Logits Accuracy: 0.8615
- Validation Start Logits Accuracy: 0.9035
- Epoch: 6

## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 9744, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 0.7982     | 0.7889                    | 0.8252                      | 0.4654          | 0.8587                         | 0.9119                           | 0     |
| 0.6087     | 0.8296                    | 0.8619                      | 0.4771          | 0.8587                         | 0.9063                           | 1     |
| 0.4630     | 0.8631                    | 0.8954                      | 0.5086          | 0.8671                         | 0.9119                           | 2     |
| 0.3575     | 0.8913                    | 0.9164                      | 0.5528          | 0.8615                         | 0.8993                           | 3     |
| 0.2690     | 0.9131                    | 0.9313                      | 0.5861          | 0.8545                         | 0.9035                           | 4     |
| 0.2047     | 0.9312                    | 0.9485                      | 0.6629          | 0.8601                         | 0.9021                           | 5     |
| 0.1588     | 0.9455                    | 0.9579                      | 0.6655          | 0.8615                         | 0.9035                           | 6     |


### Framework versions

- Transformers 4.32.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3