---
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilhubert-finetuned-mixed-data
  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. -->

# distilhubert-finetuned-mixed-data

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
- Loss: 0.7808755040168762,
- Accuracy: 0.8644688644688645,
- F1: 0.8641694609590086,
- Precision: 0.8653356589517041,
- Recall: 0.8644688644688645,
- Confusion Matrix: [[71, 9, 0, 3], [5, 42, 12, 0], [0, 7, 55, 0], [1, 0, 0, 68]]

## 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: 0.0005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 123
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Confusion Matrix                                              |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------------------------------------------------:|
| 0.5098        | 40.0000 | 50   | 0.7809          | 0.8645   | 0.8642 | 0.8653    | 0.8645 | [[71, 9, 0, 3], [5, 42, 12, 0], [0, 7, 55, 0], [1, 0, 0, 68]] |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1