---
license: apache-2.0
base_model: veriga/distilbert-base-uncased-finetuned-cola
tags:
- generated_from_keras_callback
model-index:
- name: veriga
  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. -->

# veriga

This model is a fine-tuned version of [veriga/distilbert-base-uncased-finetuned-cola](https://huggingface.co/veriga/distilbert-base-uncased-finetuned-cola) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.9335
- Train Sparse Categorical Accuracy: 0.4537
- Validation Loss: 1.9743
- Validation Sparse Categorical Accuracy: 0.4488
- 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', 'learning_rate': 5e-05, 'decay': 0.0, '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 |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 1.9359     | 0.4543                            | 1.9947          | 0.4505                                 | 0     |
| 1.9330     | 0.4547                            | 1.9796          | 0.4514                                 | 1     |
| 1.9335     | 0.4537                            | 1.9743          | 0.4488                                 | 2     |


### Framework versions

- Transformers 4.36.2
- TensorFlow 2.8.2
- Datasets 2.2.2
- Tokenizers 0.15.0