---
license: apache-2.0
base_model: albert/albert-base-v1
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: toxigen-albert-binary-clsf
  results: []
datasets:
- toxigen/toxigen-data
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/octoopt/huggingface/runs/39ugf5uc)
# toxigen-albert-binary-clsf

This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0000
- Recall: 1.0000
- Accuracy: 1.0000

## Model description

More information needed

## Intended uses & limitations

Finetuning `albert/albert-base-v1` on the `toxigen/toxigen-data` dataset on the task of binary classfication.

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|
| 0.0           | 1.0   | 3137 | 0.0000          | 1.0000    | 1.0000 | 1.0000   |
| 0.0001        | 2.0   | 6274 | 0.0000          | 1.0000    | 1.0000 | 1.0000   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1