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library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: causalbench_code-bert-base-uncased
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. -->
# causalbench_code-bert-base-uncased
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5691
- Accuracy: 0.7080
- Macro F1: 0.7030
## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log | 1.0 | 393 | 0.5905 | 0.6985 | 0.6954 |
| 0.6177 | 2.0 | 786 | 0.5688 | 0.7080 | 0.7030 |
| 0.5476 | 3.0 | 1179 | 0.5918 | 0.7048 | 0.7017 |
| 0.4672 | 4.0 | 1572 | 0.6354 | 0.7017 | 0.6920 |
| 0.4672 | 5.0 | 1965 | 0.6883 | 0.7010 | 0.6948 |
### Framework versions
- Transformers 5.17.0
- Pytorch 2.14.0+cu130
- Datasets 3.6.0
- Tokenizers 0.23.2
|