| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: fine_tune_distilbert-base-uncased |
| | results: [] |
| | datasets: |
| | - stanfordnlp/imdb |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # fine_tune_distilbert-base-uncased |
| |
|
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.1226 |
| | - Model Preparation Time: 0.0016 |
| |
|
| | ## 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 |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------------:| |
| | | 2.5551 | 1.0 | 767 | 2.3648 | 0.0016 | |
| | | 2.4329 | 2.0 | 1534 | 2.3181 | 0.0016 | |
| | | 2.3874 | 3.0 | 2301 | 2.2831 | 0.0016 | |
| | | 2.3409 | 4.0 | 3068 | 2.2422 | 0.0016 | |
| | | 2.3124 | 5.0 | 3835 | 2.2302 | 0.0016 | |
| | | 2.2895 | 6.0 | 4602 | 2.2104 | 0.0016 | |
| | | 2.2649 | 7.0 | 5369 | 2.2014 | 0.0016 | |
| | | 2.2445 | 8.0 | 6136 | 2.1939 | 0.0016 | |
| | | 2.234 | 9.0 | 6903 | 2.1776 | 0.0016 | |
| | | 2.2142 | 10.0 | 7670 | 2.1607 | 0.0016 | |
| | | 2.208 | 11.0 | 8437 | 2.1682 | 0.0016 | |
| | | 2.1933 | 12.0 | 9204 | 2.1530 | 0.0016 | |
| | | 2.1808 | 13.0 | 9971 | 2.1493 | 0.0016 | |
| | | 2.1689 | 14.0 | 10738 | 2.1422 | 0.0016 | |
| | | 2.1598 | 15.0 | 11505 | 2.1347 | 0.0016 | |
| | | 2.1567 | 16.0 | 12272 | 2.1373 | 0.0016 | |
| | | 2.1458 | 17.0 | 13039 | 2.1270 | 0.0016 | |
| | | 2.1475 | 18.0 | 13806 | 2.1200 | 0.0016 | |
| | | 2.141 | 19.0 | 14573 | 2.1312 | 0.0016 | |
| | | 2.1423 | 20.0 | 15340 | 2.1202 | 0.0016 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.44.2 |
| | - Pytorch 2.2.0+cu121 |
| | - Datasets 2.21.0 |
| | - Tokenizers 0.19.1 |
