109 lines
3.6 KiB
Markdown
109 lines
3.6 KiB
Markdown
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---
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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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guidance_scale: 1.01
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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: A meme is
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example_title: meme
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- text: >-
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Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
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He chose her because she had
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example_title: Coreference resolution
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- text: >-
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On a shelf, there are five books: a gray book, a red book, a purple book,
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a blue book, and a black book
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example_title: Logic puzzles
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- text: >-
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The two men running to become New York City's next mayor will face off in
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their first debate Wednesday night
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example_title: Reading comprehension
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pipeline_tag: text-generation
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license: apache-2.0
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language:
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- en
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---
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# pythia-31m-KI_v1-2048-scratch
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Initialized from random weights based on config of [EleutherAI/pythia-31m](https://huggingface.co/EleutherAI/pythia-31m), 3 epochs bf16
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It achieves the following results on the evaluation set:
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- Loss: 4.6160
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- Accuracy: 0.2448
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## Model description
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More information needed
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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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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 80085
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
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- lr_scheduler_type: inverse_sqrt
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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 6.3874 | 0.16 | 100 | 6.4212 | 0.1487 |
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| 5.7088 | 0.32 | 200 | 5.7926 | 0.1725 |
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| 5.4575 | 0.48 | 300 | 5.5160 | 0.1903 |
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| 5.2451 | 0.64 | 400 | 5.3429 | 0.1995 |
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| 5.0954 | 0.8 | 500 | 5.2109 | 0.2059 |
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| 5.0358 | 0.96 | 600 | 5.1068 | 0.2123 |
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| 4.94 | 1.12 | 700 | 5.0321 | 0.2157 |
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| 4.8532 | 1.28 | 800 | 4.9605 | 0.2202 |
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| 4.7602 | 1.44 | 900 | 4.9047 | 0.224 |
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| 4.6965 | 1.6 | 1000 | 4.8526 | 0.2276 |
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| 4.6855 | 1.76 | 1100 | 4.8139 | 0.2300 |
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| 4.6573 | 1.91 | 1200 | 4.7739 | 0.2327 |
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| 4.5968 | 2.07 | 1300 | 4.7451 | 0.2346 |
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| 4.5688 | 2.23 | 1400 | 4.7152 | 0.2370 |
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| 4.5205 | 2.39 | 1500 | 4.6842 | 0.2396 |
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| 4.5369 | 2.55 | 1600 | 4.6598 | 0.2410 |
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| 4.5106 | 2.71 | 1700 | 4.6352 | 0.2433 |
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| 4.4375 | 2.87 | 1800 | 4.6160 | 0.2448 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_pszemraj__pythia-31m-KI_v1-2048-scratch)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 25.21 |
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| ARC (25-shot) | 23.12 |
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| HellaSwag (10-shot) | 25.23 |
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| MMLU (5-shot) | 23.12 |
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| TruthfulQA (0-shot) | 51.67 |
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| Winogrande (5-shot) | 51.78 |
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| GSM8K (5-shot) | 0.0 |
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| DROP (3-shot) | 1.52 |
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