| --- |
| license: apache-2.0 |
| base_model: line-corporation/line-distilbert-base-japanese |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: fc-binary-model |
| 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. --> |
|
|
| # fc-binary-model |
|
|
| This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3017 |
| - Accuracy: 0.8730 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 64 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - distributed_type: tpu |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 306 | 0.3749 | 0.8594 | |
| | 0.4009 | 2.0 | 612 | 0.3578 | 0.8594 | |
| | 0.4009 | 3.0 | 918 | 0.3448 | 0.8613 | |
| | 0.3811 | 4.0 | 1224 | 0.3416 | 0.8613 | |
| | 0.3694 | 5.0 | 1530 | 0.3344 | 0.8613 | |
| | 0.3694 | 6.0 | 1836 | 0.3284 | 0.8652 | |
| | 0.3623 | 7.0 | 2142 | 0.3274 | 0.8633 | |
| | 0.3623 | 8.0 | 2448 | 0.3236 | 0.8652 | |
| | 0.3566 | 9.0 | 2754 | 0.3216 | 0.8633 | |
| | 0.349 | 10.0 | 3060 | 0.3174 | 0.8691 | |
| | 0.349 | 11.0 | 3366 | 0.3145 | 0.875 | |
| | 0.3512 | 12.0 | 3672 | 0.3135 | 0.8711 | |
| | 0.3512 | 13.0 | 3978 | 0.3102 | 0.8711 | |
| | 0.3455 | 14.0 | 4284 | 0.3119 | 0.8770 | |
| | 0.3427 | 15.0 | 4590 | 0.3100 | 0.875 | |
| | 0.3427 | 16.0 | 4896 | 0.3074 | 0.8711 | |
| | 0.3366 | 17.0 | 5202 | 0.3055 | 0.875 | |
| | 0.3385 | 18.0 | 5508 | 0.3068 | 0.875 | |
| | 0.3385 | 19.0 | 5814 | 0.3065 | 0.875 | |
| | 0.3342 | 20.0 | 6120 | 0.3047 | 0.875 | |
| | 0.3342 | 21.0 | 6426 | 0.3046 | 0.8770 | |
| | 0.3313 | 22.0 | 6732 | 0.3049 | 0.875 | |
| | 0.3349 | 23.0 | 7038 | 0.3035 | 0.875 | |
| | 0.3349 | 24.0 | 7344 | 0.3029 | 0.8730 | |
| | 0.3309 | 25.0 | 7650 | 0.3031 | 0.8730 | |
| | 0.3309 | 26.0 | 7956 | 0.3026 | 0.8711 | |
| | 0.326 | 27.0 | 8262 | 0.3026 | 0.875 | |
| | 0.3271 | 28.0 | 8568 | 0.3019 | 0.8730 | |
| | 0.3271 | 29.0 | 8874 | 0.3018 | 0.8730 | |
| | 0.3308 | 30.0 | 9180 | 0.3017 | 0.8730 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.34.0 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.14.0 |
| |
