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

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: 0.4033
- Train End Logits Accuracy: 0.8959
- Train Start Logits Accuracy: 0.8678
- Validation Loss: 2.9031
- Validation End Logits Accuracy: 0.5200
- Validation Start Logits Accuracy: 0.4756
- 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': 22620, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 2.3101     | 0.5128                    | 0.5040                      | 2.0900          | 0.5237                         | 0.4869                           | 0     |
| 1.6815     | 0.5991                    | 0.5717                      | 1.9820          | 0.5390                         | 0.5048                           | 1     |
| 1.3961     | 0.6595                    | 0.6236                      | 2.0232          | 0.5424                         | 0.5110                           | 2     |
| 1.1489     | 0.7152                    | 0.6761                      | 2.1478          | 0.5322                         | 0.4948                           | 3     |
| 0.9422     | 0.7640                    | 0.7229                      | 2.2796          | 0.5336                         | 0.4918                           | 4     |
| 0.7732     | 0.8052                    | 0.7643                      | 2.4008          | 0.5180                         | 0.4767                           | 5     |
| 0.6369     | 0.8344                    | 0.8008                      | 2.6350          | 0.5010                         | 0.4572                           | 6     |
| 0.5378     | 0.8606                    | 0.8272                      | 2.6468          | 0.5339                         | 0.4905                           | 7     |
| 0.4549     | 0.8851                    | 0.8520                      | 2.8469          | 0.5146                         | 0.4677                           | 8     |
| 0.4033     | 0.8959                    | 0.8678                      | 2.9031          | 0.5200                         | 0.4756                           | 9     |


### Framework versions

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