---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-cola

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: 0.5539
- Accuracy: 0.8169
- F1: 0.8741
- Precision: 0.8329
- Recall: 0.9196
- Matthews Correlation: 0.5504

## 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: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:--------------------:|
| 0.5215        | 1.0   | 535  | 0.4659          | 0.7747   | 0.8514 | 0.7826    | 0.9334 | 0.4284               |
| 0.3554        | 2.0   | 1070 | 0.4588          | 0.8073   | 0.8646 | 0.8403    | 0.8904 | 0.5339               |
| 0.2373        | 3.0   | 1605 | 0.5539          | 0.8169   | 0.8741 | 0.8329    | 0.9196 | 0.5504               |
| 0.1736        | 4.0   | 2140 | 0.7879          | 0.8111   | 0.8723 | 0.8187    | 0.9334 | 0.5321               |
| 0.1293        | 5.0   | 2675 | 0.8469          | 0.8102   | 0.8699 | 0.8265    | 0.9182 | 0.5324               |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3