transformers pytorch tensorboard bert 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: v10_bert-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: 0.8455882352941176
      name: Accuracy
    - type: f1
      value: 0.8923076923076922
      name: F1
---

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# v10_bert-base-uncased-finetuned-mrpc

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5079
- Accuracy: 0.8456
- F1: 0.8923

## 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: 32
- eval_batch_size: 32
- seed: 79
- 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   | 115  | 0.5043          | 0.7574   | 0.8319 |
| No log        | 2.0   | 230  | 0.4095          | 0.8456   | 0.8919 |
| No log        | 3.0   | 345  | 0.4298          | 0.8407   | 0.8889 |
| No log        | 4.0   | 460  | 0.4580          | 0.8529   | 0.8962 |
| 0.3409        | 5.0   | 575  | 0.5079          | 0.8456   | 0.8923 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3
