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---
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: 0.0254
- Train Sparse Categorical Accuracy: 0.9922
- Validation Loss: 0.3001
- Validation Sparse Categorical Accuracy: 0.9276
- Epoch: 4
## 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 |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.2755 | 0.8848 | 0.1893 | 0.9269 | 0 |
| 0.1537 | 0.9419 | 0.1946 | 0.9244 | 1 |
| 0.0822 | 0.9723 | 0.2246 | 0.9211 | 2 |
| 0.0437 | 0.9865 | 0.2782 | 0.9240 | 3 |
| 0.0254 | 0.9922 | 0.3001 | 0.9276 | 4 |
### Framework versions
- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3