metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert/distilbert-base-uncased
metrics:
- accuracy
model-index:
- name: prompt_fine_tuned_boolq
results: []
prompt_fine_tuned_boolq
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: 0.6522
- Accuracy: 0.7778
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 12 | 0.7220 | 0.2222 |
| No log | 2.0 | 24 | 0.6952 | 0.5 |
| No log | 3.0 | 36 | 0.6732 | 0.7778 |
| No log | 4.0 | 48 | 0.6600 | 0.7778 |
| No log | 5.0 | 60 | 0.6539 | 0.7778 |
| No log | 6.0 | 72 | 0.6522 | 0.7778 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1