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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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metrics: |
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- accuracy |
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language: |
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- en |
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datasets: |
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- BEE-spoke-data/UltraTextbooks-2.1-fw_mix |
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- BEE-spoke-data/napierone-epub-raw |
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- BEE-spoke-data/knowledge-inoc-concat-v1 |
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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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temperature: 0.7 |
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repetition_penalty: 1.10 |
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no_repeat_ngram_size: 6 |
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eta_cutoff: 0.0008 |
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renormalize_logits: true |
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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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--- |
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# mega-ar-350m-v0.13 |
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## Model description |
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Continued-training of [BEE-spoke-data/mega-ar-350m-L3t-v0.08-ultraTBfw](https://hf.co/BEE-spoke-data/mega-ar-350m-L3t-v0.08-ultraTBfw) on a few more datasets. |
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It achieves the following results on the evaluation set (`BEE-spoke-data/UltraTextbooks-2.1-fw_mix`): |
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- Loss: 1.9926 |
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- Accuracy: 0.5885 |
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- Num Input Tokens Seen: 3468165120 |
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## Quick eval |
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Quick eval for: pszemraj/mega-ar-350m-v0.13 |
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hf (pretrained=pszemraj/mega-ar-350m-v0.13,trust_remote_code=True,dtype=float), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 8 |
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| Tasks |Version|Filter|n-shot| Metric | Value | |Stderr| |
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|--------------|------:|------|-----:|----------|------:|---|-----:| |
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|arc_easy | 1|none | 0|acc | 0.4491|± |0.0102| |
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| | |none | 0|acc_norm | 0.4061|± |0.0101| |
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|boolq | 2|none | 0|acc | 0.5367|± |0.0087| |
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|lambada_openai| 1|none | 0|perplexity|55.3308|± |2.3100| |
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| | |none | 0|acc | 0.3113|± |0.0065| |
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|openbookqa | 1|none | 0|acc | 0.1760|± |0.0170| |
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| | |none | 0|acc_norm | 0.2680|± |0.0198| |
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|piqa | 1|none | 0|acc | 0.6366|± |0.0112| |
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| | |none | 0|acc_norm | 0.6213|± |0.0113| |
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|winogrande | 1|none | 0|acc | 0.5036|± |0.0141| |
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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: 5e-05 |
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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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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 96 |
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- total_eval_batch_size: 3 |
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- optimizer: Adam with betas=(0.9,0.985) and epsilon=1e-08 |
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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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