transformers safetensors bert text-classification generated_from_trainer dataset:glue base_model:google-bert/bert-base-uncased base_model:finetune:google-bert/bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: bert-base-uncased
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-mrpc-epochs-10-lr-5e-05
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: train
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.83
      name: Accuracy
    - type: f1
      value: 0.8794326241134751
      name: F1
---

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# bert-base-uncased-mrpc-epochs-10-lr-5e-05

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: 1.1650
- Accuracy: 0.83
- F1: 0.8794

## 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: 32
- eval_batch_size: 32
- seed: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 112  | 0.4455          | 0.77     | 0.8414 |
| No log        | 2.0   | 224  | 0.4557          | 0.8      | 0.8611 |
| No log        | 3.0   | 336  | 0.6409          | 0.8      | 0.8551 |
| No log        | 4.0   | 448  | 0.6648          | 0.82     | 0.8767 |
| 0.2723        | 5.0   | 560  | 0.8845          | 0.84     | 0.8873 |
| 0.2723        | 6.0   | 672  | 0.9873          | 0.84     | 0.8841 |
| 0.2723        | 7.0   | 784  | 1.0540          | 0.83     | 0.8777 |
| 0.2723        | 8.0   | 896  | 1.0712          | 0.85     | 0.8921 |
| 0.0161        | 9.0   | 1008 | 1.1467          | 0.84     | 0.8857 |
| 0.0161        | 10.0  | 1120 | 1.1650          | 0.83     | 0.8794 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
