---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: claim_extractor_distilbert
  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. -->

# claim_extractor_distilbert

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: 0.0859
- Train Sparse Categorical Accuracy: 0.9708
- Validation Loss: 0.2284
- Validation Sparse Categorical Accuracy: 0.9244
- 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': 1e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.2731     | 0.8882                            | 0.1975          | 0.9200                                 | 0     |
| 0.1554     | 0.9437                            | 0.1929          | 0.9229                                 | 1     |
| 0.0859     | 0.9708                            | 0.2284          | 0.9244                                 | 2     |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3