---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-mouse-enhancers
  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. -->

# distilbert-mouse-enhancers

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.5

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 242   | 0.6932          | 0.5      |
| No log        | 2.0   | 484   | 0.6949          | 0.5      |
| 0.693         | 3.0   | 726   | 0.6931          | 0.5      |
| 0.693         | 4.0   | 968   | 0.6931          | 0.5      |
| 0.694         | 5.0   | 1210  | 0.6932          | 0.5      |
| 0.694         | 6.0   | 1452  | 0.6935          | 0.5      |
| 0.6954        | 7.0   | 1694  | 0.6933          | 0.5      |
| 0.6954        | 8.0   | 1936  | 0.6932          | 0.5      |
| 0.6937        | 9.0   | 2178  | 0.6932          | 0.5      |
| 0.6937        | 10.0  | 2420  | 0.6932          | 0.5      |
| 0.6935        | 11.0  | 2662  | 0.6932          | 0.5      |
| 0.6935        | 12.0  | 2904  | 0.6934          | 0.5      |
| 0.6955        | 13.0  | 3146  | 0.6932          | 0.5      |
| 0.6955        | 14.0  | 3388  | 0.6931          | 0.5      |
| 0.6941        | 15.0  | 3630  | 0.6931          | 0.5      |
| 0.6941        | 16.0  | 3872  | 0.6932          | 0.5      |
| 0.6953        | 17.0  | 4114  | 0.6932          | 0.5      |
| 0.6953        | 18.0  | 4356  | 0.6931          | 0.5      |
| 0.6932        | 19.0  | 4598  | 0.6932          | 0.5      |
| 0.6932        | 20.0  | 4840  | 0.6931          | 0.5      |
| 0.6945        | 21.0  | 5082  | 0.6933          | 0.5      |
| 0.6945        | 22.0  | 5324  | 0.6932          | 0.5      |
| 0.6939        | 23.0  | 5566  | 0.6931          | 0.5      |
| 0.6939        | 24.0  | 5808  | 0.6931          | 0.5      |
| 0.6951        | 25.0  | 6050  | 0.6932          | 0.5      |
| 0.6951        | 26.0  | 6292  | 0.6931          | 0.5      |
| 0.6943        | 27.0  | 6534  | 0.6932          | 0.5      |
| 0.6943        | 28.0  | 6776  | 0.6931          | 0.5      |
| 0.6944        | 29.0  | 7018  | 0.6931          | 0.5      |
| 0.6944        | 30.0  | 7260  | 0.6932          | 0.5      |
| 0.6955        | 31.0  | 7502  | 0.6931          | 0.5      |
| 0.6955        | 32.0  | 7744  | 0.6933          | 0.5      |
| 0.6955        | 33.0  | 7986  | 0.6932          | 0.5      |
| 0.694         | 34.0  | 8228  | 0.6931          | 0.5      |
| 0.694         | 35.0  | 8470  | 0.6932          | 0.5      |
| 0.6937        | 36.0  | 8712  | 0.6932          | 0.5      |
| 0.6937        | 37.0  | 8954  | 0.6931          | 0.5      |
| 0.6923        | 38.0  | 9196  | 0.6932          | 0.5      |
| 0.6923        | 39.0  | 9438  | 0.6932          | 0.5      |
| 0.6931        | 40.0  | 9680  | 0.6931          | 0.5      |
| 0.6931        | 41.0  | 9922  | 0.6932          | 0.5      |
| 0.6937        | 42.0  | 10164 | 0.6932          | 0.5      |
| 0.6937        | 43.0  | 10406 | 0.6932          | 0.5      |
| 0.6936        | 44.0  | 10648 | 0.6932          | 0.5      |
| 0.6936        | 45.0  | 10890 | 0.6932          | 0.5      |
| 0.6933        | 46.0  | 11132 | 0.6932          | 0.5      |
| 0.6933        | 47.0  | 11374 | 0.6932          | 0.5      |
| 0.6924        | 48.0  | 11616 | 0.6932          | 0.5      |
| 0.6924        | 49.0  | 11858 | 0.6932          | 0.5      |
| 0.6929        | 50.0  | 12100 | 0.6932          | 0.5      |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.0
- Tokenizers 0.13.3