---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: albert-base-v2-finetuned-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. -->

# albert-base-v2-finetuned-mrpc

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6790
- Accuracy: 0.8824
- F1: 0.9161

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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   | 230  | 0.4008          | 0.8725   | 0.9113 |
| No log        | 2.0   | 460  | 0.4873          | 0.8799   | 0.9114 |
| 0.1743        | 3.0   | 690  | 0.6790          | 0.8824   | 0.9161 |
| 0.1743        | 4.0   | 920  | 0.7307          | 0.8775   | 0.9117 |
| 0.0455        | 5.0   | 1150 | 0.7307          | 0.8775   | 0.9117 |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2