--- library_name: transformers tags: - generated_from_trainer metrics: - accuracy - bleu model-index: - name: parallel-mean-bottleneck-gpt2-medium-wikitext results: [] --- # parallel-mean-bottleneck-gpt2-medium-wikitext This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.1861 - Accuracy: 0.4193 - Perplexity: 24.1930 - Bleu: 0.1440 ## 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: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Use OptimizerNames.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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Perplexity | Bleu | |:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:| | 6.0438 | 0.2806 | 500 | 5.9200 | 0.1897 | 372.4009 | 0.0359 | | 5.0422 | 0.5612 | 1000 | 4.8934 | 0.2636 | 133.4091 | 0.0610 | | 4.3494 | 0.8418 | 1500 | 4.2389 | 0.3183 | 69.3337 | 0.0833 | | 3.9486 | 1.1223 | 2000 | 3.8856 | 0.3521 | 48.6953 | 0.1037 | | 3.7605 | 1.4029 | 2500 | 3.7143 | 0.3671 | 41.0301 | 0.1206 | | 3.6544 | 1.6835 | 3000 | 3.5898 | 0.3781 | 36.2282 | 0.1332 | | 3.5527 | 1.9641 | 3500 | 3.5051 | 0.3862 | 33.2836 | 0.1349 | | 3.4346 | 2.2447 | 4000 | 3.4410 | 0.3919 | 31.2181 | 0.1335 | | 3.374 | 2.5253 | 4500 | 3.3867 | 0.3972 | 29.5672 | 0.1354 | | 3.3442 | 2.8058 | 5000 | 3.3410 | 0.4017 | 28.2468 | 0.1405 | | 3.2251 | 3.0864 | 5500 | 3.3072 | 0.4055 | 27.3093 | 0.1404 | | 3.2187 | 3.3670 | 6000 | 3.2781 | 0.4088 | 26.5242 | 0.1401 | | 3.1975 | 3.6476 | 6500 | 3.2494 | 0.4118 | 25.7753 | 0.1433 | | 3.172 | 3.9282 | 7000 | 3.2276 | 0.4142 | 25.2178 | 0.1445 | | 3.1055 | 4.2088 | 7500 | 3.2109 | 0.4163 | 24.8014 | 0.1447 | | 3.0676 | 4.4893 | 8000 | 3.1977 | 0.4178 | 24.4763 | 0.1453 | | 3.0779 | 4.7699 | 8500 | 3.1861 | 0.4193 | 24.1930 | 0.1440 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.6.0+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0