---
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: 2.9679
- Accuracy: 0.4494

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 263  | 2.0873          | 0.3483   |
| 1.9438        | 2.0   | 526  | 1.9461          | 0.4157   |
| 1.9438        | 3.0   | 789  | 1.9642          | 0.4382   |
| 1.5822        | 4.0   | 1052 | 3.0854          | 0.4270   |
| 1.5822        | 5.0   | 1315 | 2.9679          | 0.4494   |


### Framework versions

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