---
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lenate_model_12_albert-base-v2
  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. -->

# lenate_model_12_albert-base-v2

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5494
- Accuracy: 0.7622

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 355  | 0.6467          | 0.7212   |
| 0.7746        | 2.0   | 710  | 0.5847          | 0.7241   |
| 0.5448        | 3.0   | 1065 | 0.5494          | 0.7622   |
| 0.5448        | 4.0   | 1420 | 0.6416          | 0.7368   |
| 0.3705        | 5.0   | 1775 | 0.6439          | 0.7735   |
| 0.2112        | 6.0   | 2130 | 0.8791          | 0.7643   |
| 0.2112        | 7.0   | 2485 | 1.1350          | 0.7657   |
| 0.1012        | 8.0   | 2840 | 1.3247          | 0.7721   |
| 0.0294        | 9.0   | 3195 | 1.4469          | 0.7699   |
| 0.0112        | 10.0  | 3550 | 1.4783          | 0.7699   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2