---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: intent-classifyV2
  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. -->

# intent-classifyV2

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0041
- Accuracy: 0.9961
- Precision: 0.9961
- Recall: 0.9961
- F1: 0.9961

## 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: 1e-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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 64   | 0.0093          | 1.0      | 1.0       | 1.0    | 1.0    |
| No log        | 2.0   | 128  | 0.0057          | 0.9961   | 0.9961    | 0.9961 | 0.9961 |
| No log        | 3.0   | 192  | 0.0066          | 0.9961   | 0.9961    | 0.9961 | 0.9961 |
| No log        | 4.0   | 256  | 0.0041          | 0.9961   | 0.9961    | 0.9961 | 0.9961 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2