--- license: mit base_model: kennethge123/superglue_rte-gpt2 tags: - generated_from_trainer datasets: - bigbench metrics: - accuracy model-index: - name: entailed_after_rte-gpt2 results: - task: name: Text Classification type: text-classification dataset: name: bigbench type: bigbench config: entailed_polarity split: validation args: entailed_polarity metrics: - name: Accuracy type: accuracy value: 0.7142857142857143 --- # entailed_after_rte-gpt2 This model is a fine-tuned version of [kennethge123/superglue_rte-gpt2](https://huggingface.co/kennethge123/superglue_rte-gpt2) on the bigbench dataset. It achieves the following results on the evaluation set: - Loss: 1.1865 - Accuracy: 0.7143 ## 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: 4 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 30 | 0.9025 | 0.3571 | | No log | 2.0 | 60 | 0.7155 | 0.5 | | No log | 3.0 | 90 | 1.0014 | 0.2857 | | No log | 4.0 | 120 | 0.9748 | 0.5714 | | No log | 5.0 | 150 | 0.9511 | 0.5714 | | No log | 6.0 | 180 | 1.0164 | 0.6429 | | No log | 7.0 | 210 | 1.6015 | 0.5 | | No log | 8.0 | 240 | 1.2833 | 0.6429 | | No log | 9.0 | 270 | 1.0093 | 0.7857 | | No log | 10.0 | 300 | 1.6339 | 0.6429 | | No log | 11.0 | 330 | 1.3461 | 0.5714 | | No log | 12.0 | 360 | 1.2949 | 0.6429 | | No log | 13.0 | 390 | 1.6343 | 0.6429 | | No log | 14.0 | 420 | 0.8418 | 0.8571 | | No log | 15.0 | 450 | 0.6750 | 0.8571 | | No log | 16.0 | 480 | 2.0221 | 0.6429 | | 0.5929 | 17.0 | 510 | 0.7579 | 0.8571 | | 0.5929 | 18.0 | 540 | 1.5713 | 0.7143 | | 0.5929 | 19.0 | 570 | 1.0489 | 0.7143 | | 0.5929 | 20.0 | 600 | 1.1865 | 0.7143 | ### Framework versions - Transformers 4.37.0 - Pytorch 1.13.1+cu117 - Datasets 2.15.0 - Tokenizers 0.15.2