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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: 2.2501
- Validation Loss: 4.2690
- Epoch: 35
## 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 |
| 3.5337 | 4.2061 | 18 |
| 3.4483 | 4.1943 | 19 |
| 3.3589 | 4.1787 | 20 |
| 3.2776 | 4.1684 | 21 |
| 3.1959 | 4.1764 | 22 |
| 3.1161 | 4.1673 | 23 |
| 3.0389 | 4.1643 | 24 |
| 2.9631 | 4.1647 | 25 |
| 2.8859 | 4.1639 | 26 |
| 2.8110 | 4.1737 | 27 |
| 2.7362 | 4.1677 | 28 |
| 2.6631 | 4.1952 | 29 |
| 2.5915 | 4.2045 | 30 |
| 2.5227 | 4.1999 | 31 |
| 2.4573 | 4.2159 | 32 |
| 2.3862 | 4.2372 | 33 |
| 2.3205 | 4.2358 | 34 |
| 2.2501 | 4.2690 | 35 |
### Framework versions
- Transformers 4.44.0
- TensorFlow 2.16.1
- Datasets 2.21.0
- Tokenizers 0.19.1
|