---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased_latest_Nov2023
  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. -->

# distilbert-base-uncased_latest_Nov2023

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3732
- Accuracy: 0.746

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.654         | 0.2   | 100  | 0.5822          | 0.564    |
| 0.5426        | 0.4   | 200  | 0.4772          | 0.7125   |
| 0.4676        | 0.6   | 300  | 0.4183          | 0.724    |
| 0.4283        | 0.8   | 400  | 0.4053          | 0.715    |
| 0.4192        | 1.0   | 500  | 0.3918          | 0.7285   |
| 0.4063        | 1.2   | 600  | 0.3871          | 0.734    |
| 0.3752        | 1.4   | 700  | 0.3873          | 0.747    |
| 0.3779        | 1.6   | 800  | 0.3734          | 0.749    |
| 0.357         | 1.8   | 900  | 0.3754          | 0.736    |
| 0.3359        | 2.0   | 1000 | 0.3732          | 0.746    |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1