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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MC_proteome_literature_classification_balanced

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: 2.5645
- Accuracy: 0.1818

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 264  | 2.5648          | 0.1705   |
| 2.568         | 2.0   | 528  | 2.5778          | 0.1136   |
| 2.568         | 3.0   | 792  | 2.5649          | 0.0568   |
| 2.5603        | 4.0   | 1056 | 2.5649          | 0.0341   |
| 2.5603        | 5.0   | 1320 | 2.5649          | 0.1705   |
| 2.5693        | 6.0   | 1584 | 2.5649          | 0.1136   |
| 2.5693        | 7.0   | 1848 | 2.5649          | 0.1705   |
| 2.5751        | 8.0   | 2112 | 2.5649          | 0.1818   |
| 2.5751        | 9.0   | 2376 | 2.5649          | 0.1932   |
| 2.5749        | 10.0  | 2640 | 2.5649          | 0.1591   |
| 2.5749        | 11.0  | 2904 | 2.5649          | 0.1932   |
| 2.5653        | 12.0  | 3168 | 2.5649          | 0.1818   |
| 2.5653        | 13.0  | 3432 | 2.5648          | 0.1818   |
| 2.5694        | 14.0  | 3696 | 2.5647          | 0.1818   |
| 2.5694        | 15.0  | 3960 | 2.5645          | 0.1818   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3