--- license: apache-2.0 tags: - generated_from_trainer widget: - text: "I am the best; my sister is the worst. What am I?\nperson beta:\n\n" example_title: "sister" - text: "What do you call an alligator who's just had surgery to remove his left arm?\nperson beta:\n\n" example_title: "alligator" - text: "A man walks into a bar and asks for a drink. The bartender asks for $10, and he pays him $1. What did he pay him with?\nperson beta:\n\n" example_title: "dollar" - text: "What did I say was in the mailbox when it was actually in the cabinet?\nperson beta:\n\n" example_title: "mailbox" - text: "My friend says that she knows every language, but she doesn't speak any of them.. what's wrong with her?\nperson beta:\n\n." example_title: "language" - text: "I know you're tired, but can we go for another walk this evening?\nperson beta:\n\n" example_title: "walk" - text: "I have two daughters. The older one is married to a doctor, and the younger one is married to a lawyer. What is the name of my son-in-law?\nperson beta:\n\n" example_title: "riddle" - text: "My first is in Asia, my second is in Europe, my third is in North America, and my fourth is in South America. What am I?\nperson beta:\n\n" example_title: "continent" - text: "Can you take me for dinner somewhere nice this time?\nperson beta:\n\n" example_title: "dinner" - text: "Honey, I have clogged the toilet for the third time this month.. sorry..\nperson beta:\n\n" example_title: "overflow" - text: "A man pushes his car to a hotel and tells the owner he's bankrupt. Why?\nperson beta:\n\n" example_title: "brain teaser" inference: parameters: min_length: 2 max_length: 64 length_penalty: 0.7 no_repeat_ngram_size: 3 do_sample: True top_p: 0.90 top_k: 15 repetition_penalty: 2.1 --- # distilgpt2-Converse_DS-WoW_Ep-30_Bs-32 This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.2461 ## 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: 32 - eval_batch_size: 32 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | No log | 1.0 | 418 | 2.7793 | | 2.9952 | 2.0 | 836 | 2.6914 | | 2.7684 | 3.0 | 1254 | 2.6348 | | 2.685 | 4.0 | 1672 | 2.5938 | | 2.6243 | 5.0 | 2090 | 2.5625 | | 2.5816 | 6.0 | 2508 | 2.5332 | | 2.5816 | 7.0 | 2926 | 2.5098 | | 2.545 | 8.0 | 3344 | 2.4902 | | 2.5083 | 9.0 | 3762 | 2.4707 | | 2.4793 | 10.0 | 4180 | 2.4551 | | 2.4531 | 11.0 | 4598 | 2.4395 | | 2.4269 | 12.0 | 5016 | 2.4238 | | 2.4269 | 13.0 | 5434 | 2.4102 | | 2.4051 | 14.0 | 5852 | 2.3945 | | 2.3777 | 15.0 | 6270 | 2.3848 | | 2.3603 | 16.0 | 6688 | 2.3711 | | 2.3394 | 17.0 | 7106 | 2.3613 | | 2.3206 | 18.0 | 7524 | 2.3516 | | 2.3206 | 19.0 | 7942 | 2.3398 | | 2.3026 | 20.0 | 8360 | 2.3301 | | 2.2823 | 21.0 | 8778 | 2.3203 | | 2.2669 | 22.0 | 9196 | 2.3105 | | 2.2493 | 23.0 | 9614 | 2.3027 | | 2.2334 | 24.0 | 10032 | 2.2930 | | 2.2334 | 25.0 | 10450 | 2.2852 | | 2.2194 | 26.0 | 10868 | 2.2754 | | 2.2014 | 27.0 | 11286 | 2.2695 | | 2.1868 | 28.0 | 11704 | 2.2598 | | 2.171 | 29.0 | 12122 | 2.2539 | | 2.1597 | 30.0 | 12540 | 2.2461 | ### Framework versions - Transformers 4.16.1 - Pytorch 1.10.0+cu111 - Tokenizers 0.11.0