--- library_name: transformers language: - en base_model: Hartunka/distilbert_rand_5_v2 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: distilbert_rand_5_v2_sst2 results: - task: name: Text Classification type: text-classification dataset: name: GLUE SST2 type: glue args: sst2 metrics: - name: Accuracy type: accuracy value: 0.8188073394495413 --- # distilbert_rand_5_v2_sst2 This model is a fine-tuned version of [Hartunka/distilbert_rand_5_v2](https://huggingface.co/Hartunka/distilbert_rand_5_v2) on the GLUE SST2 dataset. It achieves the following results on the evaluation set: - Loss: 0.4528 - Accuracy: 0.8188 ## 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: 256 - eval_batch_size: 256 - seed: 10 - 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 - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3883 | 1.0 | 264 | 0.4528 | 0.8188 | | 0.2203 | 2.0 | 528 | 0.4741 | 0.8188 | | 0.1626 | 3.0 | 792 | 0.5146 | 0.8085 | | 0.123 | 4.0 | 1056 | 0.5761 | 0.8268 | | 0.0957 | 5.0 | 1320 | 0.6311 | 0.8096 | | 0.0747 | 6.0 | 1584 | 0.6833 | 0.8028 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.21.1