|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
base_model: bert-base-cased |
|
model-index: |
|
- name: BERT-TextClassification |
|
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. --> |
|
|
|
# BERT-TextClassification |
|
|
|
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: 0.3769 |
|
- Accuracy: 0.841 |
|
|
|
## 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 | 0.6928 | 0.518 | |
|
| No log | 2.0 | 250 | 0.6834 | 0.573 | |
|
| No log | 3.0 | 375 | 0.6808 | 0.534 | |
|
| 0.6958 | 4.0 | 500 | 0.6763 | 0.533 | |
|
| 0.6958 | 5.0 | 625 | 0.6564 | 0.639 | |
|
| 0.6958 | 6.0 | 750 | 0.6368 | 0.672 | |
|
| 0.6958 | 7.0 | 875 | 0.6091 | 0.699 | |
|
| 0.6446 | 8.0 | 1000 | 0.5769 | 0.713 | |
|
| 0.6446 | 9.0 | 1125 | 0.5434 | 0.73 | |
|
| 0.6446 | 10.0 | 1250 | 0.5142 | 0.748 | |
|
| 0.6446 | 11.0 | 1375 | 0.4820 | 0.757 | |
|
| 0.5224 | 12.0 | 1500 | 0.4638 | 0.785 | |
|
| 0.5224 | 13.0 | 1625 | 0.4383 | 0.792 | |
|
| 0.5224 | 14.0 | 1750 | 0.4222 | 0.804 | |
|
| 0.5224 | 15.0 | 1875 | 0.4121 | 0.816 | |
|
| 0.4233 | 16.0 | 2000 | 0.3995 | 0.826 | |
|
| 0.4233 | 17.0 | 2125 | 0.3958 | 0.822 | |
|
| 0.4233 | 18.0 | 2250 | 0.3886 | 0.833 | |
|
| 0.4233 | 19.0 | 2375 | 0.3843 | 0.832 | |
|
| 0.3784 | 20.0 | 2500 | 0.3820 | 0.835 | |
|
| 0.3784 | 21.0 | 2625 | 0.3804 | 0.834 | |
|
| 0.3784 | 22.0 | 2750 | 0.3784 | 0.836 | |
|
| 0.3784 | 23.0 | 2875 | 0.3773 | 0.84 | |
|
| 0.3621 | 24.0 | 3000 | 0.3771 | 0.841 | |
|
| 0.3621 | 25.0 | 3125 | 0.3769 | 0.841 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
