---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: transient_data
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# transient_data

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:
- Loss: 0.7541
- Accuracy: 0.7980

## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 204  | 0.1647          | 0.9579   |
| No log        | 1.0   | 204  | 0.6233          | 0.8001   |
| No log        | 2.0   | 408  | 0.1083          | 0.9699   |
| No log        | 2.0   | 408  | 0.7254          | 0.7910   |
| 0.2523        | 3.0   | 612  | 0.0809          | 0.9797   |
| 0.2523        | 3.0   | 612  | 0.7541          | 0.7980   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cpu
- Datasets 2.17.1
- Tokenizers 0.15.2