metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-finetuned-spam
results: []
bert-finetuned-spam
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.4740
- F1: 0.0
- Precision: 0.0
- Recall: 0.0
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: 2.984949946835231e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 1044 | nan | 0.4740 | 0.0 | 0.0 | 0.0 |
| 0.0 | 2.0 | 2088 | nan | 0.4740 | 0.0 | 0.0 | 0.0 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1