| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - massive |
| metrics: |
| - accuracy |
| model-index: |
| - name: BERT-tiny-Massive-intent |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: massive |
| type: massive |
| config: en-US |
| split: train |
| args: en-US |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8475159862272503 |
| --- |
| |
| <!-- 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-tiny-Massive-intent |
|
|
| This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the massive dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6740 |
| - Accuracy: 0.8475 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 33 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 50 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 3.6104 | 1.0 | 720 | 3.0911 | 0.3601 | |
| | 2.8025 | 2.0 | 1440 | 2.3800 | 0.5165 | |
| | 2.2292 | 3.0 | 2160 | 1.9134 | 0.5991 | |
| | 1.818 | 4.0 | 2880 | 1.5810 | 0.6744 | |
| | 1.5171 | 5.0 | 3600 | 1.3522 | 0.7108 | |
| | 1.2876 | 6.0 | 4320 | 1.1686 | 0.7442 | |
| | 1.1049 | 7.0 | 5040 | 1.0355 | 0.7683 | |
| | 0.9623 | 8.0 | 5760 | 0.9466 | 0.7885 | |
| | 0.8424 | 9.0 | 6480 | 0.8718 | 0.7875 | |
| | 0.7473 | 10.0 | 7200 | 0.8107 | 0.8028 | |
| | 0.6735 | 11.0 | 7920 | 0.7710 | 0.8180 | |
| | 0.6085 | 12.0 | 8640 | 0.7404 | 0.8210 | |
| | 0.5536 | 13.0 | 9360 | 0.7180 | 0.8229 | |
| | 0.5026 | 14.0 | 10080 | 0.6980 | 0.8318 | |
| | 0.4652 | 15.0 | 10800 | 0.6970 | 0.8337 | |
| | 0.4234 | 16.0 | 11520 | 0.6822 | 0.8372 | |
| | 0.3987 | 17.0 | 12240 | 0.6691 | 0.8436 | |
| | 0.3707 | 18.0 | 12960 | 0.6679 | 0.8455 | |
| | 0.3433 | 19.0 | 13680 | 0.6740 | 0.8475 | |
| | 0.3206 | 20.0 | 14400 | 0.6760 | 0.8451 | |
| | 0.308 | 21.0 | 15120 | 0.6704 | 0.8436 | |
| | 0.2813 | 22.0 | 15840 | 0.6701 | 0.8416 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.22.1 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.1 |
| - Tokenizers 0.12.1 |
|
|
