metadata
library_name: transformers
license: apache-2.0
base_model: albert/albert-base-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: a58af9b811decb15de671183c4b54b07
results: []
a58af9b811decb15de671183c4b54b07
This model is a fine-tuned version of 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
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 |
|---|---|---|---|---|---|---|---|
| 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 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1