| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - massive |
| metrics: |
| - f1 |
| model-index: |
| - name: data_laundry |
| 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: 0.7982630095389778 |
| --- |
| |
| <!-- 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. --> |
|
|
| # data_laundry |
| |
| This model is a fine-tuned version of [](https://huggingface.co/) on the massive dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0394 |
| - F1: 0.7983 |
| |
| ## 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: 0.001 |
| - 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:| |
| | 5.4021 | 0.5 | 719 | 4.2520 | 0.1592 | |
| | 3.5936 | 1.0 | 1438 | 3.0222 | 0.4171 | |
| | 2.6221 | 1.5 | 2157 | 2.2881 | 0.5433 | |
| | 2.1941 | 2.0 | 2876 | 2.0383 | 0.6238 | |
| | 1.8688 | 2.5 | 3595 | 1.7730 | 0.6562 | |
| | 1.7334 | 3.0 | 4314 | 1.6450 | 0.6885 | |
| | 1.5359 | 3.5 | 5033 | 1.5398 | 0.7121 | |
| | 1.4867 | 3.99 | 5752 | 1.4296 | 0.7324 | |
| | 1.353 | 4.49 | 6471 | 1.3721 | 0.7393 | |
| | 1.3088 | 4.99 | 7190 | 1.3110 | 0.7530 | |
| | 1.2006 | 5.49 | 7909 | 1.2633 | 0.7482 | |
| | 1.1845 | 5.99 | 8628 | 1.2417 | 0.7635 | |
| | 1.111 | 6.49 | 9347 | 1.2015 | 0.7795 | |
| | 1.0722 | 6.99 | 10066 | 1.1605 | 0.7813 | |
| | 1.0121 | 7.49 | 10785 | 1.1383 | 0.7781 | |
| | 1.018 | 7.99 | 11504 | 1.1024 | 0.7990 | |
| | 0.9202 | 8.49 | 12223 | 1.0905 | 0.7898 | |
| | 0.9639 | 8.99 | 12942 | 1.0695 | 0.7967 | |
| | 0.915 | 9.49 | 13661 | 1.0444 | 0.7935 | |
| | 0.8743 | 9.99 | 14380 | 1.0394 | 0.7983 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.34.0.dev0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.14.5 |
| - Tokenizers 0.14.0 |
|
|
