---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: customer-support-intent-albert
  results: []
widget:
- text: "please help me change several items of an order"
  example_title: "example 1"
- text: "i need the invoice of the last order"
  example_title: "example 2"
- text: "can you please change the shipping address"
  example_title: "example 3"
---

<!-- 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. -->

# customer-support-intent-albert

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) for intent classification on the [bitext/Bitext-customer-support-llm-chatbot-training-dataset](https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset) dataset.

It achieves the following results on the evaluation set:
- Loss: 0.0154
- Accuracy: 0.9988

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1993        | 1.0   | 409  | 0.0969          | 0.9927   |
| 0.0304        | 2.0   | 818  | 0.0247          | 0.9951   |
| 0.0087        | 3.0   | 1227 | 0.0169          | 0.9963   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3