metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
- accuracy
- f1
model-index:
- name: loha_fine_tuned_copa
results: []
loha_fine_tuned_copa
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: 0.6922
- Accuracy: 0.5
- F1: 0.5
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
- training_steps: 400
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7089 | 1.0 | 50 | 0.6923 | 0.5 | 0.5 |
| 0.7026 | 2.0 | 100 | 0.6923 | 0.5 | 0.5 |
| 0.6995 | 3.0 | 150 | 0.6923 | 0.5 | 0.5 |
| 0.7009 | 4.0 | 200 | 0.6923 | 0.5 | 0.5 |
| 0.6997 | 5.0 | 250 | 0.6923 | 0.5 | 0.5 |
| 0.7028 | 6.0 | 300 | 0.6922 | 0.5 | 0.5 |
| 0.6951 | 7.0 | 350 | 0.6922 | 0.5 | 0.5 |
| 0.6949 | 8.0 | 400 | 0.6922 | 0.5 | 0.5 |
Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1