| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: bert-base-uncased-issues-128 |
| | 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-issues-128 |
| |
|
| | 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: 1.2432 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 16 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 2.0987 | 1.0 | 291 | 1.6066 | |
| | | 1.631 | 2.0 | 582 | 1.4775 | |
| | | 1.4933 | 3.0 | 873 | 1.4646 | |
| | | 1.3984 | 4.0 | 1164 | 1.3314 | |
| | | 1.3377 | 5.0 | 1455 | 1.3122 | |
| | | 1.274 | 6.0 | 1746 | 1.2062 | |
| | | 1.2538 | 7.0 | 2037 | 1.2626 | |
| | | 1.192 | 8.0 | 2328 | 1.1832 | |
| | | 1.1612 | 9.0 | 2619 | 1.2055 | |
| | | 1.1489 | 10.0 | 2910 | 1.1605 | |
| | | 1.1262 | 11.0 | 3201 | 1.1925 | |
| | | 1.1022 | 12.0 | 3492 | 1.1309 | |
| | | 1.0892 | 13.0 | 3783 | 1.1692 | |
| | | 1.0812 | 14.0 | 4074 | 1.2384 | |
| | | 1.0666 | 15.0 | 4365 | 1.0822 | |
| | | 1.0533 | 16.0 | 4656 | 1.2432 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.13.0 |
| | - Pytorch 1.10.0 |
| | - Datasets 2.2.2 |
| | - Tokenizers 0.10.3 |
| |
|
