| --- |
| base_model: intfloat/multilingual-e5-base |
| license: mit |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: multilingual-e5-base_censor_v0.1 |
| 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. --> |
|
|
| # multilingual-e5-base_censor_v0.1 |
|
|
| This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5077 |
| - Accuracy: 0.7695 |
| - Precision: 0.7729 |
| - Recall: 0.7695 |
| - F1: 0.7708 |
| - Roc Auc: 0.8424 |
| - Per Class F1: [0.8104358705451601, 0.7061407261629732] |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 3 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc | Per Class F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|:----------------------------------------:| |
| | 0.5485 | 1.0 | 2795 | 0.5249 | 0.7349 | 0.7498 | 0.7349 | 0.7383 | 0.8169 | [0.7723692804179954, 0.6827648980028912] | |
| | 0.4871 | 2.0 | 5590 | 0.5059 | 0.7610 | 0.7667 | 0.7610 | 0.7629 | 0.8362 | [0.8013980033834657, 0.7000926419808541] | |
| | 0.4392 | 3.0 | 8385 | 0.5077 | 0.7695 | 0.7729 | 0.7695 | 0.7708 | 0.8424 | [0.8104358705451601, 0.7061407261629732] | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.43.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
