| | --- |
| | library_name: peft |
| | license: apache-2.0 |
| | base_model: distilbert/distilbert-base-uncased |
| | tags: |
| | - base_model:adapter:distilbert/distilbert-base-uncased |
| | - lora |
| | - transformers |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: results |
| | results: [] |
| | datasets: |
| | - iam-tsr/employ_fdbk |
| | language: |
| | - en |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # results |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on [employ feedback dataset](https://huggingface.co/datasets/iam-tsr/employ_fdbk). |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1520 |
| | - Accuracy: 0.9423 |
| | - Precision: 0.9181 |
| | - Recall: 0.9284 |
| | - F1: 0.9228 |
| |
|
| | ## 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: 0.001 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.1735 | 1.0 | 172 | 0.1631 | 0.9462 | 0.9249 | 0.9297 | 0.9272 | |
| | | 0.1824 | 2.0 | 344 | 0.1619 | 0.9385 | 0.9108 | 0.9308 | 0.9191 | |
| | | 0.1555 | 3.0 | 516 | 0.1520 | 0.9423 | 0.9181 | 0.9284 | 0.9228 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.18.0 |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.1+cu128 |
| | - Datasets 4.3.0 |
| | - Tokenizers 0.22.2 |
