transformers pytorch safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased doi:10.57967/hf/1058 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: message-tone
  results: []
---

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# message-tone

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: 0.2719
- Accuracy: 0.9197

## 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        | 0.11  | 100  | 0.3326          | 0.903    |
| No log        | 0.21  | 200  | 0.3056          | 0.9087   |
| No log        | 0.32  | 300  | 0.2854          | 0.9153   |
| No log        | 0.43  | 400  | 0.2846          | 0.9153   |
| 0.3712        | 0.53  | 500  | 0.2808          | 0.9177   |
| 0.3712        | 0.64  | 600  | 0.2769          | 0.9187   |
| 0.3712        | 0.75  | 700  | 0.2781          | 0.9187   |
| 0.3712        | 0.85  | 800  | 0.2740          | 0.9197   |
| 0.3712        | 0.96  | 900  | 0.2719          | 0.9197   |


### Framework versions

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