|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: bert-base-uncased |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
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-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.5319 |
|
|
|
|
|
## 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: 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 |
|
|
- training_steps: 1377 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| No log | 0.1089 | 50 | 0.5885 | |
|
|
| 0.6475 | 0.2179 | 100 | 0.5992 | |
|
|
| 0.6475 | 0.3268 | 150 | 0.5555 | |
|
|
| 0.5984 | 0.4357 | 200 | 0.5674 | |
|
|
| 0.5984 | 0.5447 | 250 | 0.8102 | |
|
|
| 0.574 | 0.6536 | 300 | 0.5246 | |
|
|
| 0.574 | 0.7625 | 350 | 0.5154 | |
|
|
| 0.5728 | 0.8715 | 400 | 0.5616 | |
|
|
| 0.5728 | 0.9804 | 450 | 0.5247 | |
|
|
| 0.4933 | 1.0893 | 500 | 0.4771 | |
|
|
| 0.4933 | 1.1983 | 550 | 0.5082 | |
|
|
| 0.4332 | 1.3072 | 600 | 0.4866 | |
|
|
| 0.4332 | 1.4161 | 650 | 0.4762 | |
|
|
| 0.4269 | 1.5251 | 700 | 0.3891 | |
|
|
| 0.4269 | 1.6340 | 750 | 0.4092 | |
|
|
| 0.3825 | 1.7429 | 800 | 0.4439 | |
|
|
| 0.3825 | 1.8519 | 850 | 0.3988 | |
|
|
| 0.4038 | 1.9608 | 900 | 0.4035 | |
|
|
| 0.4038 | 2.0697 | 950 | 0.5283 | |
|
|
| 0.2891 | 2.1786 | 1000 | 0.5314 | |
|
|
| 0.2891 | 2.2876 | 1050 | 0.5842 | |
|
|
| 0.2558 | 2.3965 | 1100 | 0.5879 | |
|
|
| 0.2558 | 2.5054 | 1150 | 0.5792 | |
|
|
| 0.2529 | 2.6144 | 1200 | 0.5626 | |
|
|
| 0.2529 | 2.7233 | 1250 | 0.5591 | |
|
|
| 0.2729 | 2.8322 | 1300 | 0.5504 | |
|
|
| 0.2729 | 2.9412 | 1350 | 0.5319 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.55.4 |
|
|
- Pytorch 2.7.1 |
|
|
- Datasets 4.0.0 |
|
|
- Tokenizers 0.21.4 |
|
|
|
