---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: hfnlpmodels/eos_prediction_distilbert_1
  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. -->

# hfnlpmodels/eos_prediction_distilbert_1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0879
- Train Accuracy: 0.9714
- Validation Loss: 0.2180
- Validation Accuracy: 0.9305
- Epoch: 2

## Model description

Predicts (or should predict) whether a given sentence is complete. Trained on sentences that were randomly truncate as '0' labels, hence some sentences which were grammatically correct may have been labelled as incomplete. Overall accuracy near 0.9 means that this was most likely a small factor.

## Intended uses & limitations

Found better performance on shorter sentences.

## 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': 4165, '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 Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.2709     | 0.8942         | 0.2015          | 0.9211              | 0     |
| 0.1421     | 0.9505         | 0.2055          | 0.9318              | 1     |
| 0.0879     | 0.9714         | 0.2180          | 0.9305              | 2     |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Tokenizers 0.15.2