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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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widget: |
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- text: "I know you're tired, but can we go for another walk this evening?\nperson beta:\n\n" |
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example_title: "walk" |
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- 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" |
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example_title: "riddle" |
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- 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" |
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example_title: "continent" |
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- text: "Can you take me for dinner somewhere nice this time?\nperson beta:\n\n" |
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example_title: "dinner" |
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- text: "Honey, I have clogged the toilet for the third time this month.. sorry..\nperson beta:\n\n" |
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example_title: "overflow" |
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- text: "A man pushes his car to a hotel and tells the owner he's bankrupt. Why?\nperson beta:\n\n" |
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example_title: "brain teaser" |
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- text: "I am the best; my sister is the worst. What am I?\nperson beta:\n\n" |
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example_title: "sister" |
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- text: "What do you call an alligator who's just had surgery to remove his left arm?\nperson beta:\n\n" |
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example_title: "alligator" |
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- 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" |
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example_title: "dollar" |
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- text: "What did I say was in the mailbox when it was actually in the cabinet?\nperson beta:\n\n" |
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example_title: "mailbox" |
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- 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." |
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example_title: "language" |
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- text: "I know you're tired, but can we go for another walk this evening?\nperson beta:\n\n" |
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example_title: "walk" |
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- 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" |
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inference: |
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parameters: |
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min_length: 2 |
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max_length: 64 |
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length_penalty: 0.7 |
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no_repeat_ngram_size: 3 |
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do_sample: True |
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top_p: 0.90 |
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top_k: 15 |
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repetition_penalty: 2.1 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilgpt2-tiny-conversational |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on a parsed version of Wizard of Wikipedia. Persona alpha/beta framework designed for use with [ai-msgbot](https://github.com/pszemraj/ai-msgbot). |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2461 |
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## Model description |
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- it is a splendid model |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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- deepspeed |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| No log | 1.0 | 418 | 2.7793 | |
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| 2.9952 | 2.0 | 836 | 2.6914 | |
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| 2.7684 | 3.0 | 1254 | 2.6348 | |
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| 2.685 | 4.0 | 1672 | 2.5938 | |
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| 2.6243 | 5.0 | 2090 | 2.5625 | |
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| 2.5816 | 6.0 | 2508 | 2.5332 | |
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| 2.5816 | 7.0 | 2926 | 2.5098 | |
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| 2.545 | 8.0 | 3344 | 2.4902 | |
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| 2.5083 | 9.0 | 3762 | 2.4707 | |
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| 2.4793 | 10.0 | 4180 | 2.4551 | |
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| 2.4531 | 11.0 | 4598 | 2.4395 | |
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| 2.4269 | 12.0 | 5016 | 2.4238 | |
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| 2.4269 | 13.0 | 5434 | 2.4102 | |
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| 2.4051 | 14.0 | 5852 | 2.3945 | |
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| 2.3777 | 15.0 | 6270 | 2.3848 | |
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| 2.3603 | 16.0 | 6688 | 2.3711 | |
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| 2.3394 | 17.0 | 7106 | 2.3613 | |
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| 2.3206 | 18.0 | 7524 | 2.3516 | |
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| 2.3206 | 19.0 | 7942 | 2.3398 | |
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| 2.3026 | 20.0 | 8360 | 2.3301 | |
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| 2.2823 | 21.0 | 8778 | 2.3203 | |
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| 2.2669 | 22.0 | 9196 | 2.3105 | |
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| 2.2493 | 23.0 | 9614 | 2.3027 | |
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| 2.2334 | 24.0 | 10032 | 2.2930 | |
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| 2.2334 | 25.0 | 10450 | 2.2852 | |
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| 2.2194 | 26.0 | 10868 | 2.2754 | |
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| 2.2014 | 27.0 | 11286 | 2.2695 | |
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| 2.1868 | 28.0 | 11704 | 2.2598 | |
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| 2.171 | 29.0 | 12122 | 2.2539 | |
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| 2.1597 | 30.0 | 12540 | 2.2461 | |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu111 |
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- Tokenizers 0.11.0 |
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