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

# trainer

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: 0.6671
- Accuracy: {'accuracy': 0.6136936111747194}

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy                         |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
| 0.6652        | 1.0   | 5096  | 0.6672          | {'accuracy': 0.6136936111747194} |
| 0.6621        | 2.0   | 10192 | 0.6675          | {'accuracy': 0.6136936111747194} |
| 0.6702        | 3.0   | 15288 | 0.6711          | {'accuracy': 0.6136936111747194} |
| 0.6748        | 4.0   | 20384 | 0.6705          | {'accuracy': 0.6136936111747194} |
| 0.6693        | 5.0   | 25480 | 0.6674          | {'accuracy': 0.6136936111747194} |
| 0.6594        | 6.0   | 30576 | 0.6672          | {'accuracy': 0.6136936111747194} |
| 0.6663        | 7.0   | 35672 | 0.6682          | {'accuracy': 0.6136936111747194} |
| 0.6738        | 8.0   | 40768 | 0.6671          | {'accuracy': 0.6136936111747194} |
| 0.6669        | 9.0   | 45864 | 0.6671          | {'accuracy': 0.6136936111747194} |
| 0.6654        | 10.0  | 50960 | 0.6671          | {'accuracy': 0.6136936111747194} |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2