metadata
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: []
bert-base-uncased-FinedTuned
This model is a fine-tuned version of 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