| | --- |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: office-character |
| | 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. --> |
| |
|
| | # office-character |
| |
|
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.4745 |
| | - Accuracy: 0.1565 |
| | - F1: 0.1477 |
| |
|
| | ## 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: 20 |
| | - eval_batch_size: 20 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 2.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | 2.5676 | 0.26 | 100 | 2.5803 | 0.0774 | 0.0111 | |
| | | 2.5531 | 0.51 | 200 | 2.5176 | 0.1252 | 0.0967 | |
| | | 2.5032 | 0.77 | 300 | 2.4914 | 0.1322 | 0.1155 | |
| | | 2.4291 | 1.03 | 400 | 2.4709 | 0.1391 | 0.1223 | |
| | | 2.2983 | 1.28 | 500 | 2.4680 | 0.1504 | 0.1415 | |
| | | 2.2439 | 1.54 | 600 | 2.4774 | 0.1478 | 0.1415 | |
| | | 2.1867 | 1.79 | 700 | 2.4745 | 0.1565 | 0.1477 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.32.1 |
| | - Pytorch 2.0.1 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
