---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sms_class_test9
  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. -->

# sms_class_test9

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0058
- Accuracy: 0.9987
- F1: 0.9987
- Precision: 0.9988
- Recall: 0.9987

## 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: 32
- eval_batch_size: 32
- 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 225  | 0.0227          | 0.9950   | 0.9950 | 0.9951    | 0.9950 |
| No log        | 2.0   | 450  | 0.0077          | 0.9987   | 0.9987 | 0.9988    | 0.9987 |
| 0.0506        | 3.0   | 675  | 0.0047          | 0.9987   | 0.9987 | 0.9988    | 0.9987 |
| 0.0506        | 4.0   | 900  | 0.0058          | 0.9987   | 0.9987 | 0.9988    | 0.9987 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3