| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: 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. --> |
|
|
| # model |
|
|
| 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: 3.2354 |
| - Accuracy: 0.5933 |
| - Macro F1: 0.5949 |
|
|
| ## 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 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 0.8639 | 1.0 | 748 | 0.8235 | 0.6094 | 0.6099 | |
| | 0.6838 | 2.0 | 1496 | 0.8541 | 0.6348 | 0.6278 | |
| | 0.4318 | 3.0 | 2244 | 1.0577 | 0.6147 | 0.6125 | |
| | 0.3233 | 4.0 | 2992 | 1.6734 | 0.6020 | 0.6031 | |
| | 0.2183 | 5.0 | 3740 | 2.0912 | 0.6074 | 0.6087 | |
| | 0.161 | 6.0 | 4488 | 2.5560 | 0.5926 | 0.5946 | |
| | 0.08 | 7.0 | 5236 | 2.8546 | 0.5846 | 0.5880 | |
| | 0.1 | 8.0 | 5984 | 3.1178 | 0.5826 | 0.5864 | |
| | 0.0343 | 9.0 | 6732 | 3.1232 | 0.5987 | 0.5969 | |
| | 0.0712 | 10.0 | 7480 | 3.2354 | 0.5933 | 0.5949 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.41.2 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
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|
