| | --- |
| | 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 |
| |
|
