| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: albert/albert-base-v1 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: a58af9b811decb15de671183c4b54b07 |
| 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. --> |
|
|
| # a58af9b811decb15de671183c4b54b07 |
|
|
| This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on the contemmcm/amazon_reviews_2013 [cell-phone] dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8621 |
| - Data Size: 1.0 |
| - Epoch Runtime: 72.8094 |
| - Accuracy: 0.6829 |
| - F1 Macro: 0.6121 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
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| More information needed |
|
|
| ## Training and evaluation data |
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| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------------:|:--------:|:--------:| |
| | No log | 0 | 0 | 1.7944 | 0 | 5.8050 | 0.1102 | 0.0716 | |
| | No log | 1 | 1973 | 1.4652 | 0.0078 | 6.7679 | 0.3875 | 0.1904 | |
| | 0.0319 | 2 | 3946 | 1.3011 | 0.0156 | 7.0154 | 0.4623 | 0.2680 | |
| | 1.1769 | 3 | 5919 | 1.1409 | 0.0312 | 7.9874 | 0.5376 | 0.3510 | |
| | 0.9719 | 4 | 7892 | 0.9420 | 0.0625 | 9.9755 | 0.6041 | 0.4954 | |
| | 0.8939 | 5 | 9865 | 0.8626 | 0.125 | 14.2018 | 0.6356 | 0.5305 | |
| | 0.8639 | 6 | 11838 | 0.8189 | 0.25 | 22.6114 | 0.6580 | 0.5508 | |
| | 0.8509 | 7 | 13811 | 0.7834 | 0.5 | 39.4226 | 0.6698 | 0.6019 | |
| | 0.7676 | 8.0 | 15784 | 0.7777 | 1.0 | 73.1966 | 0.6729 | 0.6116 | |
| | 0.6876 | 9.0 | 17757 | 0.7524 | 1.0 | 74.0192 | 0.6952 | 0.6125 | |
| | 0.6258 | 10.0 | 19730 | 0.7636 | 1.0 | 75.1704 | 0.6802 | 0.6244 | |
| | 0.6055 | 11.0 | 21703 | 0.7913 | 1.0 | 73.2826 | 0.6909 | 0.6220 | |
| | 0.5316 | 12.0 | 23676 | 0.7981 | 1.0 | 73.7851 | 0.6908 | 0.6192 | |
| | 0.4656 | 13.0 | 25649 | 0.8621 | 1.0 | 72.8094 | 0.6829 | 0.6121 | |
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| ### Framework versions |
|
|
| - Transformers 4.57.0 |
| - Pytorch 2.8.0+cu128 |
| - Datasets 4.2.0 |
| - Tokenizers 0.22.1 |
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|
