---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: muhtasham/small-mlm-glue-mnli
model-index:
- name: small-mlm-glue-mnli-target-glue-mrpc
  results: []
---

<!-- 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. -->

# small-mlm-glue-mnli-target-glue-mrpc

This model is a fine-tuned version of [muhtasham/small-mlm-glue-mnli](https://huggingface.co/muhtasham/small-mlm-glue-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9598
- Accuracy: 0.7721
- F1: 0.8432

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3946        | 4.35  | 500  | 0.8309          | 0.7647   | 0.8476 |
| 0.0715        | 8.7   | 1000 | 1.3662          | 0.7647   | 0.8405 |
| 0.0285        | 13.04 | 1500 | 1.6659          | 0.7647   | 0.8405 |
| 0.0149        | 17.39 | 2000 | 1.8421          | 0.7696   | 0.8396 |
| 0.0158        | 21.74 | 2500 | 1.9587          | 0.7647   | 0.8426 |
| 0.0152        | 26.09 | 3000 | 2.0488          | 0.7672   | 0.848  |
| 0.0147        | 30.43 | 3500 | 1.9463          | 0.7770   | 0.8535 |
| 0.0096        | 34.78 | 4000 | 1.7938          | 0.7819   | 0.8529 |
| 0.0124        | 39.13 | 4500 | 1.8361          | 0.7868   | 0.8538 |
| 0.0152        | 43.48 | 5000 | 1.9598          | 0.7721   | 0.8432 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2