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---
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
should probably proofread and complete it, then remove this comment. -->

# 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: 3.6012
- Accuracy: 0.4382

## 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   | 263  | 2.4798          | 0.2809   |
| 2.4407        | 2.0   | 526  | 2.3829          | 0.3146   |
| 2.4407        | 3.0   | 789  | 2.3702          | 0.3146   |
| 2.2844        | 4.0   | 1052 | 2.2006          | 0.3034   |
| 2.2844        | 5.0   | 1315 | 2.0415          | 0.3933   |
| 2.2551        | 6.0   | 1578 | 2.1146          | 0.3708   |
| 2.2551        | 7.0   | 1841 | 2.4420          | 0.4045   |
| 1.7206        | 8.0   | 2104 | 2.4813          | 0.4045   |
| 1.7206        | 9.0   | 2367 | 2.1333          | 0.4494   |
| 1.2881        | 10.0  | 2630 | 2.8120          | 0.4382   |
| 1.2881        | 11.0  | 2893 | 2.7040          | 0.4607   |
| 0.9473        | 12.0  | 3156 | 3.1826          | 0.4382   |
| 0.9473        | 13.0  | 3419 | 3.1203          | 0.4157   |
| 0.5293        | 14.0  | 3682 | 3.4692          | 0.4270   |
| 0.5293        | 15.0  | 3945 | 3.6012          | 0.4382   |


### Framework versions

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