---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_keras_callback
model-index:
- name: LongRiver/transformer_QAVi
  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. -->

# LongRiver/transformer_QAVi

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1280
- Train End Logits Accuracy: 0.9610
- Train Start Logits Accuracy: 0.9485
- Validation Loss: 2.0278
- Validation End Logits Accuracy: 0.6900
- Validation Start Logits Accuracy: 0.6542
- Epoch: 9

## 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': 55450, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.6102     | 0.5808                    | 0.5465                      | 1.1787          | 0.6799                         | 0.6465                           | 0     |
| 0.9934     | 0.7242                    | 0.6859                      | 1.1191          | 0.6984                         | 0.6676                           | 1     |
| 0.7428     | 0.7852                    | 0.7468                      | 1.1470          | 0.6996                         | 0.6693                           | 2     |
| 0.5627     | 0.8317                    | 0.7975                      | 1.2633          | 0.6977                         | 0.6624                           | 3     |
| 0.4244     | 0.8709                    | 0.8396                      | 1.4117          | 0.6933                         | 0.6589                           | 4     |
| 0.3229     | 0.9013                    | 0.8736                      | 1.5396          | 0.6870                         | 0.6575                           | 5     |
| 0.2478     | 0.9239                    | 0.9009                      | 1.7142          | 0.6880                         | 0.6573                           | 6     |
| 0.1909     | 0.9398                    | 0.9243                      | 1.8694          | 0.6893                         | 0.6543                           | 7     |
| 0.1526     | 0.9528                    | 0.9388                      | 1.9620          | 0.6867                         | 0.6516                           | 8     |
| 0.1280     | 0.9610                    | 0.9485                      | 2.0278          | 0.6900                         | 0.6542                           | 9     |


### Framework versions

- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2