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---
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_copa
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lora_fine_tuned_copa
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6918
- Accuracy: 0.46
- F1: 0.4570
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7088 | 1.0 | 50 | 0.6921 | 0.48 | 0.48 |
| 0.7024 | 2.0 | 100 | 0.6922 | 0.49 | 0.4894 |
| 0.6993 | 3.0 | 150 | 0.6921 | 0.46 | 0.4587 |
| 0.7005 | 4.0 | 200 | 0.6920 | 0.48 | 0.4788 |
| 0.6989 | 5.0 | 250 | 0.6919 | 0.47 | 0.4679 |
| 0.7018 | 6.0 | 300 | 0.6919 | 0.46 | 0.4570 |
| 0.6943 | 7.0 | 350 | 0.6919 | 0.46 | 0.4570 |
| 0.6943 | 8.0 | 400 | 0.6918 | 0.46 | 0.4570 |
### Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |