---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: albert_model
  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_model

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6560
- Accuracy: 0.9070
- F1: 0.8852
- Recall: 0.9122

## 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: 1e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| No log        | 1.0   | 167  | 0.3571          | 0.8351   | 0.8142 | 0.9198 |
| No log        | 2.0   | 334  | 0.2670          | 0.8891   | 0.8683 | 0.9313 |
| 0.3358        | 3.0   | 501  | 0.2643          | 0.9115   | 0.8885 | 0.8969 |
| 0.3358        | 4.0   | 668  | 0.3804          | 0.9130   | 0.8910 | 0.9046 |
| 0.3358        | 5.0   | 835  | 0.4376          | 0.9070   | 0.8848 | 0.9084 |
| 0.1007        | 6.0   | 1002 | 0.4957          | 0.9100   | 0.8859 | 0.8893 |
| 0.1007        | 7.0   | 1169 | 0.6375          | 0.8801   | 0.8601 | 0.9389 |
| 0.1007        | 8.0   | 1336 | 0.5978          | 0.8996   | 0.8780 | 0.9198 |
| 0.012         | 9.0   | 1503 | 0.6101          | 0.9025   | 0.8816 | 0.9237 |
| 0.012         | 10.0  | 1670 | 0.6209          | 0.9085   | 0.8847 | 0.8931 |
| 0.012         | 11.0  | 1837 | 0.6485          | 0.9010   | 0.8787 | 0.9122 |
| 0.0007        | 12.0  | 2004 | 0.6480          | 0.9070   | 0.8852 | 0.9122 |
| 0.0007        | 13.0  | 2171 | 0.6527          | 0.9055   | 0.8835 | 0.9122 |
| 0.0007        | 14.0  | 2338 | 0.6557          | 0.9055   | 0.8835 | 0.9122 |
| 0.0002        | 15.0  | 2505 | 0.6560          | 0.9070   | 0.8852 | 0.9122 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3