|
---
|
|
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
|
|
should probably proofread and complete it, then remove this comment. -->
|
|
|
|
# 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: 0.8412
|
|
- Accuracy: {'accuracy': 0.892}
|
|
|
|
## 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 | 0.3108 | {'accuracy': 0.889} |
|
|
| 0.4242 | 2.0 | 500 | 0.3551 | {'accuracy': 0.885} |
|
|
| 0.4242 | 3.0 | 750 | 0.4353 | {'accuracy': 0.882} |
|
|
| 0.1852 | 4.0 | 1000 | 0.5893 | {'accuracy': 0.891} |
|
|
| 0.1852 | 5.0 | 1250 | 0.6041 | {'accuracy': 0.888} |
|
|
| 0.0699 | 6.0 | 1500 | 0.7350 | {'accuracy': 0.88} |
|
|
| 0.0699 | 7.0 | 1750 | 0.8007 | {'accuracy': 0.888} |
|
|
| 0.0201 | 8.0 | 2000 | 0.8161 | {'accuracy': 0.887} |
|
|
| 0.0201 | 9.0 | 2250 | 0.8273 | {'accuracy': 0.887} |
|
|
| 0.0044 | 10.0 | 2500 | 0.8412 | {'accuracy': 0.892} |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.32.1
|
|
- Pytorch 2.3.1
|
|
- Datasets 3.2.0
|
|
- Tokenizers 0.13.3
|
|
|
