|
--- |
|
language: |
|
- nl |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- abc |
|
- generated_from_trainer |
|
datasets: |
|
- stsb_multi_mt |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert-base-uncased-FinedTuned |
|
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-base-uncased-FinedTuned |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the stsb_multi_mt dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.3210 |
|
- Accuracy: 0.1762 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 100 |
|
- training_steps: 100 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| No log | 0.0556 | 10 | 7.6479 | 0.1762 | |
|
| No log | 0.1111 | 20 | 6.9937 | 0.1762 | |
|
| 8.2277 | 0.1667 | 30 | 6.2531 | 0.1762 | |
|
| 8.2277 | 0.2222 | 40 | 5.6151 | 0.1762 | |
|
| 6.019 | 0.2778 | 50 | 4.8978 | 0.1762 | |
|
| 6.019 | 0.3333 | 60 | 3.6924 | 0.1762 | |
|
| 6.019 | 0.3889 | 70 | 2.9463 | 0.1762 | |
|
| 3.6301 | 0.4444 | 80 | 2.5056 | 0.1762 | |
|
| 3.6301 | 0.5 | 90 | 2.3194 | 0.1762 | |
|
| 2.2789 | 0.5556 | 100 | 2.3210 | 0.1762 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
