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: lora_fine_tuned_cb
results: []
lora_fine_tuned_cb
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: 1.4310
- Accuracy: 0.3182
- F1: 0.1536
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: 0.003
- 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 |
|---|---|---|---|---|---|
| 0.8568 | 3.5714 | 50 | 2.3106 | 0.3182 | 0.1536 |
| 0.8465 | 7.1429 | 100 | 1.3703 | 0.3182 | 0.1536 |
| 0.7884 | 10.7143 | 150 | 1.3701 | 0.3182 | 0.1536 |
| 0.7275 | 14.2857 | 200 | 1.5024 | 0.3182 | 0.1536 |
| 0.7691 | 17.8571 | 250 | 1.3990 | 0.3182 | 0.1536 |
| 0.742 | 21.4286 | 300 | 1.3898 | 0.3182 | 0.1536 |
| 0.7094 | 25.0 | 350 | 1.4059 | 0.3182 | 0.1536 |
| 0.7238 | 28.5714 | 400 | 1.4310 | 0.3182 | 0.1536 |
Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1