safetensors generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 region:us
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-lora-text-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-lora-text-classification

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: 0.9162
- Accuracy: {'accuracy': 0.901}

## 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            |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|
| No log        | 1.0   | 250  | 0.3611          | {'accuracy': 0.871} |
| 0.4182        | 2.0   | 500  | 0.5356          | {'accuracy': 0.883} |
| 0.4182        | 3.0   | 750  | 0.5292          | {'accuracy': 0.899} |
| 0.2132        | 4.0   | 1000 | 0.5966          | {'accuracy': 0.897} |
| 0.2132        | 5.0   | 1250 | 0.6869          | {'accuracy': 0.894} |
| 0.0748        | 6.0   | 1500 | 0.7645          | {'accuracy': 0.898} |
| 0.0748        | 7.0   | 1750 | 0.8095          | {'accuracy': 0.897} |
| 0.0335        | 8.0   | 2000 | 0.9055          | {'accuracy': 0.892} |
| 0.0335        | 9.0   | 2250 | 0.9086          | {'accuracy': 0.901} |
| 0.0083        | 10.0  | 2500 | 0.9162          | {'accuracy': 0.901} |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
