| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: finetuning-sentiment-model-distil-samples |
| 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. --> |
|
|
| # finetuning-sentiment-model-distil-samples |
|
|
| This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.3150 |
| - Accuracy Percentage: 0.7514 |
| - Accuracy Number: 133.0 |
| - F1: 0.7460 |
| - Precision: 0.7514 |
| - Recall: 0.7514 |
|
|
| ## 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: 32 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy Percentage | Accuracy Number | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:-------------------:|:---------------:|:------:|:---------:|:------:| |
| | 0.2349 | 1.0 | 22 | 0.6664 | 0.7571 | 134.0 | 0.7552 | 0.7571 | 0.7571 | |
| | 0.0531 | 2.0 | 44 | 1.0491 | 0.7232 | 128.0 | 0.7093 | 0.7232 | 0.7232 | |
| | 0.0374 | 3.0 | 66 | 1.1389 | 0.7119 | 126.0 | 0.7154 | 0.7119 | 0.7119 | |
| | 0.023 | 4.0 | 88 | 1.2514 | 0.7401 | 131.0 | 0.7288 | 0.7401 | 0.7401 | |
| | 0.0188 | 5.0 | 110 | 1.2064 | 0.7401 | 131.0 | 0.7355 | 0.7401 | 0.7401 | |
| | 0.0171 | 6.0 | 132 | 1.3531 | 0.7458 | 132.0 | 0.7365 | 0.7458 | 0.7458 | |
| | 0.0188 | 7.0 | 154 | 1.3221 | 0.7627 | 135.0 | 0.7534 | 0.7627 | 0.7627 | |
| | 0.0162 | 8.0 | 176 | 1.2874 | 0.7571 | 134.0 | 0.7507 | 0.7571 | 0.7571 | |
| | 0.018 | 9.0 | 198 | 1.2882 | 0.7627 | 135.0 | 0.7579 | 0.7627 | 0.7627 | |
| | 0.0097 | 10.0 | 220 | 1.3150 | 0.7514 | 133.0 | 0.7460 | 0.7514 | 0.7514 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
