safetensors roberta generated_from_trainer en dataset:glue base_model:FacebookAI/roberta-large base_model:finetune:FacebookAI/roberta-large model-index region:us
---
base_model: FacebookAI/roberta-large
datasets:
- glue
language:
- en
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: MRPC
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.8970588235294118
      name: Accuracy
    - type: f1
      value: 0.9257950530035336
      name: F1
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MRPC

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4089
- Accuracy: 0.8971
- F1: 0.9258
- Combined Score: 0.9114

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| No log        | 1.0   | 58   | 0.4189          | 0.8186   | 0.8783 | 0.8485         |
| No log        | 2.0   | 116  | 0.3024          | 0.8824   | 0.9140 | 0.8982         |
| No log        | 3.0   | 174  | 0.2900          | 0.8848   | 0.9174 | 0.9011         |
| No log        | 4.0   | 232  | 0.4089          | 0.8652   | 0.9076 | 0.8864         |
| No log        | 5.0   | 290  | 0.4089          | 0.8971   | 0.9258 | 0.9114         |
| No log        | 6.0   | 348  | 0.4556          | 0.8922   | 0.9233 | 0.9078         |


### Framework versions

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