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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: node-py/my_awesome_eli5_clm-model
  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. -->

# node-py/my_awesome_eli5_clm-model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.6182
- Validation Loss: 4.2285
- Epoch: 17

## 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 7.3929     | 6.0819          | 0     |
| 5.9912     | 5.8303          | 1     |
| 5.7553     | 5.5854          | 2     |
| 5.5082     | 5.3645          | 3     |
| 5.2836     | 5.1815          | 4     |
| 5.0867     | 5.0252          | 5     |
| 4.9075     | 4.8834          | 6     |
| 4.7424     | 4.7747          | 7     |
| 4.5947     | 4.6684          | 8     |
| 4.4570     | 4.5836          | 9     |
| 4.3290     | 4.5194          | 10    |
| 4.2123     | 4.4408          | 11    |
| 4.1037     | 4.3965          | 12    |
| 3.9979     | 4.3630          | 13    |
| 3.8983     | 4.3101          | 14    |
| 3.8011     | 4.2792          | 15    |
| 3.7097     | 4.2592          | 16    |
| 3.6182     | 4.2285          | 17    |


### Framework versions

- Transformers 4.44.0
- TensorFlow 2.16.1
- Datasets 2.21.0
- Tokenizers 0.19.1