---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: CuATR-distilbert-LoRA
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CuATR-distilbert-LoRA

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: 0.6921
- Accuracy: 0.6087
- F1: 0.7429

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6915        | 0.67  | 1    | 0.6924          | 0.5652   | 0.7222 |
| 0.7001        | 2.0   | 3    | 0.6922          | 0.6087   | 0.7429 |
| 0.6993        | 2.67  | 4    | 0.6921          | 0.6087   | 0.7429 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0