transformers pytorch tensorboard squeezebert text-classification generated_from_trainer dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: squeezebert-mnli-headless-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: 0.8823529411764706
      name: Accuracy
    - type: f1
      value: 0.9136690647482014
      name: F1
---

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# squeezebert-mnli-headless-finetuned-mrpc

This model is a fine-tuned version of [squeezebert/squeezebert-mnli-headless](https://huggingface.co/squeezebert/squeezebert-mnli-headless) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3142
- Accuracy: 0.8824
- F1: 0.9137

## 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: 73
- 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  | 0.4461          | 0.8162   | 0.8705 |
| No log        | 2.0   | 230  | 0.3844          | 0.8407   | 0.8866 |
| No log        | 3.0   | 345  | 0.3181          | 0.8848   | 0.9156 |
| No log        | 4.0   | 460  | 0.3159          | 0.8775   | 0.9091 |
| 0.3723        | 5.0   | 575  | 0.3142          | 0.8824   | 0.9137 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
