| | --- |
| | license: apache-2.0 |
| | base_model: distilbert/distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - massive |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: results |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: massive |
| | type: massive |
| | config: en-US |
| | split: test |
| | args: en-US |
| | metrics: |
| | - name: F1 |
| | type: f1 |
| | value: 0.9734295558770142 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # results |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the massive dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0231 |
| | - F1: 0.9734 |
| |
|
| | ## 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 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 3.8235 | 0.5 | 185 | 3.7551 | 0.0022 | |
| | | 3.5949 | 0.99 | 370 | 3.1246 | 0.0454 | |
| | | 2.8705 | 1.49 | 555 | 2.4379 | 0.1543 | |
| | | 2.3444 | 1.99 | 740 | 1.7732 | 0.2967 | |
| | | 1.7151 | 2.49 | 925 | 1.2983 | 0.4403 | |
| | | 1.3959 | 2.98 | 1110 | 0.9965 | 0.5490 | |
| | | 0.9919 | 3.48 | 1295 | 0.7098 | 0.6880 | |
| | | 0.9495 | 3.98 | 1480 | 0.5798 | 0.7014 | |
| | | 0.6 | 4.48 | 1665 | 0.4419 | 0.7408 | |
| | | 0.5952 | 4.97 | 1850 | 0.3653 | 0.7522 | |
| | | 0.3715 | 5.47 | 2035 | 0.3077 | 0.7957 | |
| | | 0.3783 | 5.97 | 2220 | 0.2050 | 0.8453 | |
| | | 0.196 | 6.47 | 2405 | 0.1532 | 0.8386 | |
| | | 0.22 | 6.96 | 2590 | 0.0968 | 0.8871 | |
| | | 0.1117 | 7.46 | 2775 | 0.0725 | 0.9057 | |
| | | 0.1065 | 7.96 | 2960 | 0.0458 | 0.9265 | |
| | | 0.0644 | 8.45 | 3145 | 0.0378 | 0.9336 | |
| | | 0.0526 | 8.95 | 3330 | 0.0324 | 0.9616 | |
| | | 0.0521 | 9.45 | 3515 | 0.0251 | 0.9708 | |
| | | 0.0302 | 9.95 | 3700 | 0.0231 | 0.9734 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.38.1 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
