---
language:
- en
base_model: google-t5/t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: MRPC
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8970588235294118
    - name: F1
      type: f1
      value: 0.926829268292683
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# MRPC

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5629
- Accuracy: 0.8971
- F1: 0.9268
- Combined Score: 0.9119

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Combined Score | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:--------------:|:------:|:---------------:|
| No log        | 1.0   | 115  | 0.7108   | 0.7671         | 0.8234 | 0.5476          |
| No log        | 2.0   | 230  | 0.8701   | 0.8901         | 0.9100 | 0.3523          |
| No log        | 3.0   | 345  | 0.8725   | 0.8924         | 0.9122 | 0.3624          |
| No log        | 4.0   | 460  | 0.8775   | 0.8949         | 0.9123 | 0.3646          |
| 0.3744        | 5.0   | 575  | 0.8946   | 0.9099         | 0.9252 | 0.4054          |
| 0.3744        | 6.0   | 690  | 0.8897   | 0.9057         | 0.9217 | 0.4624          |
| 0.3744        | 7.0   | 805  | 0.5530   | 0.8873         | 0.9212 | 0.9042          |
| 0.3744        | 8.0   | 920  | 0.5405   | 0.8897         | 0.9220 | 0.9059          |
| 0.0877        | 9.0   | 1035 | 0.5629   | 0.8971         | 0.9268 | 0.9119          |
| 0.0877        | 10.0  | 1150 | 0.5856   | 0.8922         | 0.9241 | 0.9081          |


### Framework versions

- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1