---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: message-genre
  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. -->

# message-genre

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: 1.5875
- Accuracy: 0.4339

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.06  | 100  | 1.8239          | 0.3638   |
| No log        | 0.13  | 200  | 1.7266          | 0.3971   |
| No log        | 0.19  | 300  | 1.6873          | 0.4040   |
| No log        | 0.25  | 400  | 1.6609          | 0.4188   |
| 1.8118        | 0.32  | 500  | 1.6674          | 0.4048   |
| 1.8118        | 0.38  | 600  | 1.6381          | 0.4172   |
| 1.8118        | 0.45  | 700  | 1.6437          | 0.4156   |
| 1.8118        | 0.51  | 800  | 1.6378          | 0.4143   |
| 1.8118        | 0.57  | 900  | 1.6301          | 0.4214   |
| 1.6738        | 0.64  | 1000 | 1.6106          | 0.4320   |
| 1.6738        | 0.7   | 1100 | 1.6089          | 0.4259   |
| 1.6738        | 0.76  | 1200 | 1.5988          | 0.4299   |
| 1.6738        | 0.83  | 1300 | 1.5951          | 0.4347   |
| 1.6738        | 0.89  | 1400 | 1.5896          | 0.4320   |
| 1.6488        | 0.96  | 1500 | 1.5875          | 0.4339   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3