| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - accuracy |
| - f1 |
| model-index: |
| - name: bert-base-phia-secondhandDescription-1000 |
| 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. --> |
|
|
| # bert-base-phia-secondhandDescription-1000 |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9318 |
| - Precision: 0.8414 |
| - Recall: 0.8311 |
| - Accuracy: 0.8311 |
| - F1: 0.8306 |
|
|
| ## 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: 10 |
| - eval_batch_size: 10 |
| - 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 | Precision | Recall | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:| |
| | No log | 1.0 | 84 | 1.4608 | 0.7781 | 0.6824 | 0.6824 | 0.6766 | |
| | No log | 2.0 | 168 | 0.7149 | 0.8298 | 0.8176 | 0.8176 | 0.8185 | |
| | 1.4174 | 3.0 | 252 | 0.6704 | 0.8229 | 0.8041 | 0.8041 | 0.8036 | |
| | 1.4174 | 4.0 | 336 | 0.8298 | 0.8359 | 0.7973 | 0.7973 | 0.7974 | |
| | 0.2952 | 5.0 | 420 | 0.7800 | 0.8525 | 0.8311 | 0.8311 | 0.8305 | |
| | 0.2952 | 6.0 | 504 | 0.8365 | 0.8464 | 0.8311 | 0.8311 | 0.8312 | |
| | 0.2952 | 7.0 | 588 | 0.9032 | 0.8309 | 0.8176 | 0.8176 | 0.8184 | |
| | 0.0537 | 8.0 | 672 | 0.8952 | 0.8337 | 0.8243 | 0.8243 | 0.8237 | |
| | 0.0537 | 9.0 | 756 | 0.9206 | 0.8414 | 0.8311 | 0.8311 | 0.8306 | |
| | 0.0243 | 10.0 | 840 | 0.9318 | 0.8414 | 0.8311 | 0.8311 | 0.8306 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.42.3 |
| - Pytorch 2.3.1 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
|
|
