metadata
library_name: peft
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results_lora
results: []
results_lora
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2809
- Accuracy: 0.8922
- F1: 0.8965
- Precision: 0.8772
- Recall: 0.9167
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2818 | 1.0 | 4210 | 0.2717 | 0.8888 | 0.8904 | 0.8934 | 0.8874 |
| 0.2723 | 2.0 | 8420 | 0.2880 | 0.8888 | 0.8945 | 0.8653 | 0.9257 |
| 0.2321 | 3.0 | 12630 | 0.2809 | 0.8922 | 0.8965 | 0.8772 | 0.9167 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1