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--- |
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license: apache-2.0 |
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base_model: pszemraj/mega-ar-small-4096-NC-simplewiki-v1 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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inference: |
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parameters: |
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max_new_tokens: 64 |
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do_sample: true |
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repetition_penalty: 1.1 |
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no_repeat_ngram_size: 5 |
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eta_cutoff: 0.001 |
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widget: |
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- text: My name is El Microondas the Wise and |
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example_title: El Microondas |
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- text: Kennesaw State University is a public |
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example_title: Kennesaw State University |
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- text: >- |
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Bungie Studios is an American video game developer. They are most famous for |
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developing the award winning Halo series of video games. They also made |
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Destiny. The studio was founded |
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example_title: Bungie |
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- text: The Mona Lisa is a world-renowned painting created by |
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example_title: Mona Lisa |
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- text: >- |
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The Harry Potter series, written by J.K. Rowling, begins with the book |
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titled |
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example_title: Harry Potter Series |
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- text: >- |
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Question: I have cities, but no houses. I have mountains, but no trees. I |
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have water, but no fish. What am I? |
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Answer: |
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example_title: Riddle |
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- text: The process of photosynthesis involves the conversion of |
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example_title: Photosynthesis |
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- text: >- |
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Jane went to the store to buy some groceries. She picked up apples, oranges, |
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and a loaf of bread. When she got home, she realized she forgot |
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example_title: Story Continuation |
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- text: >- |
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Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph, and |
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another train leaves Station B at 10:00 AM and travels at 80 mph, when will |
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they meet if the distance between the stations is 300 miles? |
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To determine |
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example_title: Math Problem |
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- text: In the context of computer programming, an algorithm is |
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example_title: Algorithm Definition |
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pipeline_tag: text-generation |
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datasets: |
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- JeanKaddour/minipile |
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- pszemraj/simple_wikipedia_LM |
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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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# mega-ar-small-4096-NC-minipile-v1 |
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65M parameter MEGA autoregressive model initialized from scratch and trained on: |
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1. `pszemraj/simple_wikipedia_LM` |
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2. `JeanKaddour/minipile` |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7502 |
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- Accuracy: 0.3650 |
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## eval |
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initial 'get the feet wet': |
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`hf-causal-experimental (pretrained=pszemraj/mega-ar-small-4096-sw_minipile,revision=main,trust_remote_code=True,dtype='float'), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16` |
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| Task |Version| Metric | Value | | Stderr | |
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|--------------|------:|--------|--------:|---|-------:| |
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|arc_easy | 0|acc | 0.3173|± | 0.0096| |
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| | |acc_norm| 0.3022|± | 0.0094| |
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|boolq | 1|acc | 0.4107|± | 0.0086| |
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|lambada_openai| 0|ppl |6843.1824|± |295.0792| |
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| | |acc | 0.0155|± | 0.0017| |
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|openbookqa | 0|acc | 0.1220|± | 0.0147| |
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| | |acc_norm| 0.2480|± | 0.0193| |
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|piqa | 0|acc | 0.5609|± | 0.0116| |
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| | |acc_norm| 0.5566|± | 0.0116| |
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|winogrande | 0|acc | 0.5059|± | 0.0141| |
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still some ways to go. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 80085 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1.0 |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.2.0.dev20230907+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
