--- language: - en tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: hBERTv2_new_pretrain_w_init__sst2 results: - task: name: Text Classification type: text-classification dataset: name: GLUE SST2 type: glue config: sst2 split: validation args: sst2 metrics: - name: Accuracy type: accuracy value: 0.8360091743119266 --- # hBERTv2_new_pretrain_w_init__sst2 This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_wt_init) on the GLUE SST2 dataset. It achieves the following results on the evaluation set: - Loss: 0.4105 - Accuracy: 0.8360 ## 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: 4e-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 10 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3399 | 1.0 | 527 | 0.4105 | 0.8360 | | 0.2098 | 2.0 | 1054 | 0.4837 | 0.8222 | | 0.1578 | 3.0 | 1581 | 0.5173 | 0.8119 | | 0.1219 | 4.0 | 2108 | 0.5737 | 0.8337 | | 0.0978 | 5.0 | 2635 | 0.5374 | 0.8165 | | 0.0803 | 6.0 | 3162 | 0.6070 | 0.8245 | ### Framework versions - Transformers 4.29.2 - Pytorch 1.14.0a0+410ce96 - Datasets 2.12.0 - Tokenizers 0.13.3