transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert/distilbert-base-uncased
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.8333333333333334
      name: Accuracy
    - type: f1
      value: 0.8831615120274915
      name: F1
---

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# distilbert-base-uncased_mrpc

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3859
- Accuracy: 0.8333
- F1: 0.8832
- Combined Score: 0.8582

## 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: 256
- eval_batch_size: 256
- seed: 10
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6015        | 1.0   | 15   | 0.5433          | 0.7034   | 0.8158 | 0.7596         |
| 0.4875        | 2.0   | 30   | 0.4264          | 0.8064   | 0.8501 | 0.8282         |
| 0.3682        | 3.0   | 45   | 0.3859          | 0.8333   | 0.8832 | 0.8582         |
| 0.2647        | 4.0   | 60   | 0.4190          | 0.8505   | 0.8968 | 0.8736         |
| 0.1766        | 5.0   | 75   | 0.4325          | 0.8431   | 0.8904 | 0.8668         |
| 0.1147        | 6.0   | 90   | 0.5659          | 0.8333   | 0.8840 | 0.8586         |
| 0.0731        | 7.0   | 105  | 0.7540          | 0.8309   | 0.8860 | 0.8584         |
| 0.0616        | 8.0   | 120  | 0.6755          | 0.8260   | 0.8795 | 0.8527         |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
