| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: albert/albert-base-v1 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - rouge |
| model-index: |
| - name: 1a7d904346e7c4adfb1de13434e74811 |
| 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. --> |
|
|
| # 1a7d904346e7c4adfb1de13434e74811 |
|
|
| This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on the google/boolq dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8393 |
| - Data Size: 1.0 |
| - Epoch Runtime: 11.5957 |
| - Accuracy: 0.7365 |
| - F1 Macro: 0.7092 |
| - Rouge1: 0.7365 |
| - Rouge2: 0.0 |
| - Rougel: 0.7359 |
| - Rougelsum: 0.7362 |
|
|
| ## 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 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - total_train_batch_size: 32 |
| - total_eval_batch_size: 32 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: constant |
| - num_epochs: 50 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|:------:|:------:|:------:|:---------:| |
| | No log | 0 | 0 | 0.7204 | 0 | 1.6779 | 0.4779 | 0.4482 | 0.4779 | 0.0 | 0.4782 | 0.4773 | |
| | No log | 1 | 294 | 0.7127 | 0.0078 | 3.0497 | 0.4605 | 0.4594 | 0.4602 | 0.0 | 0.4608 | 0.4602 | |
| | No log | 2 | 588 | 0.6631 | 0.0156 | 1.8627 | 0.6213 | 0.3832 | 0.6213 | 0.0 | 0.6207 | 0.6210 | |
| | No log | 3 | 882 | 0.6623 | 0.0312 | 2.0432 | 0.6222 | 0.4283 | 0.6222 | 0.0 | 0.6213 | 0.6225 | |
| | 0.0272 | 4 | 1176 | 0.6547 | 0.0625 | 2.3096 | 0.6219 | 0.3850 | 0.6219 | 0.0 | 0.6215 | 0.6216 | |
| | 0.0546 | 5 | 1470 | 0.6508 | 0.125 | 2.9116 | 0.6385 | 0.4884 | 0.6382 | 0.0 | 0.6382 | 0.6385 | |
| | 0.0898 | 6 | 1764 | 0.6159 | 0.25 | 4.1202 | 0.6615 | 0.5994 | 0.6615 | 0.0 | 0.6612 | 0.6615 | |
| | 0.5742 | 7 | 2058 | 0.5887 | 0.5 | 6.5760 | 0.6893 | 0.6685 | 0.6890 | 0.0 | 0.6893 | 0.6893 | |
| | 0.5151 | 8.0 | 2352 | 0.5455 | 1.0 | 11.4274 | 0.7230 | 0.6932 | 0.7237 | 0.0 | 0.7233 | 0.7233 | |
| | 0.4331 | 9.0 | 2646 | 0.5818 | 1.0 | 11.3375 | 0.7307 | 0.7003 | 0.7310 | 0.0 | 0.7304 | 0.7307 | |
| | 0.2983 | 10.0 | 2940 | 0.6985 | 1.0 | 11.3204 | 0.7374 | 0.7160 | 0.7381 | 0.0 | 0.7374 | 0.7374 | |
| | 0.2542 | 11.0 | 3234 | 0.7486 | 1.0 | 11.4927 | 0.7405 | 0.7218 | 0.7405 | 0.0 | 0.7405 | 0.7405 | |
| | 0.1905 | 12.0 | 3528 | 0.8393 | 1.0 | 11.5957 | 0.7365 | 0.7092 | 0.7365 | 0.0 | 0.7359 | 0.7362 | |
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| ### Framework versions |
|
|
| - Transformers 4.57.0 |
| - Pytorch 2.8.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
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|
