| | --- |
| | base_model: google-bert/bert-base-uncased |
| | library_name: peft |
| | license: apache-2.0 |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: bert-sst2-sentiment-lora |
| | 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-sst2-sentiment-lora |
| |
|
| | This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2664 |
| | - Accuracy: 0.9094 |
| | - F1: 0.9123 |
| | - Precision: 0.8993 |
| | - Recall: 0.9257 |
| |
|
| | ## 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: 16 |
| | - 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 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 0.3043 | 1.0 | 4210 | 0.2483 | 0.9128 | 0.9148 | 0.9107 | 0.9189 | |
| | | 0.2494 | 2.0 | 8420 | 0.2577 | 0.9083 | 0.9109 | 0.9009 | 0.9212 | |
| | | 0.1861 | 3.0 | 12630 | 0.2664 | 0.9094 | 0.9123 | 0.8993 | 0.9257 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.12.0 |
| | - Transformers 4.44.2 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.0.0 |
| | - Tokenizers 0.19.1 |
