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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: bert-base-cased
model-index:
- name: test_trainer
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. -->
# test_trainer
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3803
- Accuracy: 0.842
## 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: 5e-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: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 125 | 0.6786 | 0.608 |
| No log | 2.0 | 250 | 0.6718 | 0.598 |
| No log | 3.0 | 375 | 0.6695 | 0.574 |
| 0.6888 | 4.0 | 500 | 0.6583 | 0.599 |
| 0.6888 | 5.0 | 625 | 0.6262 | 0.684 |
| 0.6888 | 6.0 | 750 | 0.5936 | 0.697 |
| 0.6888 | 7.0 | 875 | 0.5520 | 0.721 |
| 0.6057 | 8.0 | 1000 | 0.5149 | 0.746 |
| 0.6057 | 9.0 | 1125 | 0.4848 | 0.762 |
| 0.6057 | 10.0 | 1250 | 0.4558 | 0.779 |
| 0.6057 | 11.0 | 1375 | 0.4346 | 0.793 |
| 0.4583 | 12.0 | 1500 | 0.4215 | 0.801 |
| 0.4583 | 13.0 | 1625 | 0.4094 | 0.815 |
| 0.4583 | 14.0 | 1750 | 0.4027 | 0.816 |
| 0.4583 | 15.0 | 1875 | 0.3962 | 0.82 |
| 0.3847 | 16.0 | 2000 | 0.3926 | 0.823 |
| 0.3847 | 17.0 | 2125 | 0.3873 | 0.835 |
| 0.3847 | 18.0 | 2250 | 0.3857 | 0.833 |
| 0.3847 | 19.0 | 2375 | 0.3823 | 0.836 |
| 0.3565 | 20.0 | 2500 | 0.3819 | 0.837 |
| 0.3565 | 21.0 | 2625 | 0.3850 | 0.837 |
| 0.3565 | 22.0 | 2750 | 0.3806 | 0.839 |
| 0.3565 | 23.0 | 2875 | 0.3801 | 0.84 |
| 0.3348 | 24.0 | 3000 | 0.3808 | 0.842 |
| 0.3348 | 25.0 | 3125 | 0.3803 | 0.842 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 |