---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-distilbert-uncased-on-HOPE
  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. -->

# finetuned-distilbert-uncased-on-HOPE

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3303
- Accuracy: 0.5429

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4925        | 1.0   | 289  | 1.4588          | 0.5140   |
| 1.2379        | 2.0   | 578  | 1.3627          | 0.5339   |
| 1.0435        | 3.0   | 867  | 1.3433          | 0.5492   |
| 1.1216        | 4.0   | 1156 | 1.3632          | 0.5357   |
| 0.9046        | 5.0   | 1445 | 1.4644          | 0.5086   |
| 0.855         | 6.0   | 1734 | 1.5160          | 0.5185   |
| 0.6505        | 7.0   | 2023 | 1.6085          | 0.5149   |
| 0.5166        | 8.0   | 2312 | 1.6686          | 0.5059   |
| 0.5659        | 9.0   | 2601 | 1.7079          | 0.5032   |
| 0.5263        | 10.0  | 2890 | 1.7293          | 0.5086   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1