| | --- |
| | license: apache-2.0 |
| | base_model: bert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: '1' |
| | 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. --> |
| |
|
| | # 1 |
| |
|
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: nan |
| | - F1: 0.0032 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: constant |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - training_steps: 200 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 9.5074 | 0.18 | 10 | nan | 0.0060 | |
| | | 8.5442 | 0.37 | 20 | nan | 0.0102 | |
| | | 6.6803 | 0.55 | 30 | nan | 0.0 | |
| | | 7.1123 | 0.73 | 40 | nan | 0.0040 | |
| | | 9.1525 | 0.92 | 50 | nan | 0.0044 | |
| | | 7.3704 | 1.1 | 60 | nan | 0.0 | |
| | | 6.0446 | 1.28 | 70 | nan | 0.0 | |
| | | 6.8367 | 1.47 | 80 | nan | 0.0 | |
| | | 6.3409 | 1.65 | 90 | nan | 0.0144 | |
| | | 7.3165 | 1.83 | 100 | nan | 0.0 | |
| | | 6.2659 | 2.02 | 110 | nan | 0.0 | |
| | | 5.7613 | 2.2 | 120 | nan | 0.0 | |
| | | 6.3813 | 2.39 | 130 | nan | 0.0044 | |
| | | 6.977 | 2.57 | 140 | nan | 0.0102 | |
| | | 6.1388 | 2.75 | 150 | nan | 0.0063 | |
| | | 8.3673 | 2.94 | 160 | nan | 0.0013 | |
| | | 6.9132 | 3.12 | 170 | nan | 0.0059 | |
| | | 7.4859 | 3.3 | 180 | nan | 0.0 | |
| | | 6.5924 | 3.49 | 190 | nan | 0.0061 | |
| | | 6.3331 | 3.67 | 200 | nan | 0.0032 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
