---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
base_model: sileod/deberta-v3-base-tasksource-nli
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: deberta-v3-bass-complex-questions_classifier
  results: []
widget:
- text: "Why did the company decide to enter the Latin America region?"
  example_title: "Simple Query"
- text: "What was the Company's net profit margin in the last fiscal year, and how does it compare to the industry average?"
  example_title: "Multiple Queries"
- text: "Compare the customer growth rates in the SaaS sector of CloudServices Inc. with that of SaaSSolutions Tech over the last two years."
  example_title: "Comparable Query"
- text: "What are your favorite ways to show friends you're thinking of them?"
  example_title: "SmallTalk Query"
- text: "Alter the proposal to emphasize sustainability practices."
  example_title: "Functional Query"
---

<!-- 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. -->

# deberta-v3-bass-complex-questions_classifier

This model is a fine-tuned version of [sileod/deberta-v3-base-tasksource-nli](https://huggingface.co/sileod/deberta-v3-base-tasksource-nli) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 0
- 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 | Precision | Recall | F1  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|
| 0.0532        | 2.3585 | 500  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.19.1