transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.8480392156862745
      name: Accuracy
    - type: f1
      value: 0.8945578231292517
      name: F1
---

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# distilbert-base-uncased-finetuned-mrpc

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4304
- Accuracy: 0.8480
- F1: 0.8946

## 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: 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 230  | 0.3851          | 0.8137   | 0.8652 |
| No log        | 2.0   | 460  | 0.3614          | 0.8456   | 0.8948 |
| 0.4318        | 3.0   | 690  | 0.4304          | 0.8480   | 0.8946 |
| 0.4318        | 4.0   | 920  | 0.5555          | 0.8407   | 0.8900 |
| 0.1697        | 5.0   | 1150 | 0.5883          | 0.8456   | 0.8927 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
