|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: distilbert-base-uncased |
|
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 the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.0657 |
|
- Accuracy: {'accuracy': 0.7330827067669173} |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:| |
|
| 0.9636 | 1.0 | 538 | 0.8582 | {'accuracy': 0.6992481203007519} | |
|
| 0.7447 | 2.0 | 1076 | 1.0010 | {'accuracy': 0.7030075187969925} | |
|
| 0.5876 | 3.0 | 1614 | 0.9129 | {'accuracy': 0.7142857142857143} | |
|
| 0.4728 | 4.0 | 2152 | 1.1641 | {'accuracy': 0.7255639097744361} | |
|
| 0.4145 | 5.0 | 2690 | 1.3646 | {'accuracy': 0.7330827067669173} | |
|
| 0.2917 | 6.0 | 3228 | 1.4447 | {'accuracy': 0.7556390977443609} | |
|
| 0.2485 | 7.0 | 3766 | 1.7574 | {'accuracy': 0.7330827067669173} | |
|
| 0.1596 | 8.0 | 4304 | 1.9367 | {'accuracy': 0.7330827067669173} | |
|
| 0.1468 | 9.0 | 4842 | 2.0091 | {'accuracy': 0.7368421052631579} | |
|
| 0.1128 | 10.0 | 5380 | 2.0657 | {'accuracy': 0.7330827067669173} | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.41.0 |
|
- Pytorch 2.3.0 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
