---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
- trl
- sft
metrics:
- 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
should probably proofread and complete it, then remove this comment. -->

# 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: 0.6691
- Matthews Correlation: 0.5171

## 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: 5.6294991226703914e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 16
- optimizer: Use OptimizerNames.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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 1.0   | 134  | 0.4796          | 0.4210               |
| No log        | 2.0   | 268  | 0.4766          | 0.5101               |
| No log        | 3.0   | 402  | 0.5300          | 0.5083               |
| 0.3001        | 4.0   | 536  | 0.6691          | 0.5171               |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.21.1