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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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license: apache-2.0 |
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datasets: |
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- pszemraj/simple_wikipedia_LM |
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pipeline_tag: text-generation |
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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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# pythia-31m-simplewiki-scratch-bf16 |
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|
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Trained from random initialized config based on [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: 4.1763 |
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- Accuracy: 0.3676 |
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## Model description |
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tuned with bf16 (previous was fp32) |
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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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``` |
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***** eval metrics ***** |
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epoch = 2.99 |
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eval_accuracy = 0.3723 eval_loss = 4.1155 |
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eval_runtime = 0:00:14.44 |
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eval_samples = 500 eval_samples_per_second = 34.602 eval_steps_per_second = 17.301 |
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perplexity = 61.2811 |
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``` |
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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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| 5.8617 | 0.45 | 100 | 5.5276 | 0.2451 | |
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| 5.2782 | 0.9 | 200 | 4.9596 | 0.2965 | |
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| 4.9996 | 1.35 | 300 | 4.6412 | 0.3310 | |
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| 4.6292 | 1.8 | 400 | 4.4344 | 0.3485 | |
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| 4.5339 | 2.25 | 500 | 4.2875 | 0.3600 | |
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| 4.5214 | 2.7 | 600 | 4.1763 | 0.3676 | |
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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 |
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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-simplewiki-scratch-bf16) |
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| Metric | Value | |
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|-----------------------|---------------------------| |
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| Avg. | 24.63 | |
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| ARC (25-shot) | 22.78 | |
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| HellaSwag (10-shot) | 25.61 | |
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| MMLU (5-shot) | 23.12 | |
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| TruthfulQA (0-shot) | 49.65 | |
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| Winogrande (5-shot) | 50.51 | |
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| GSM8K (5-shot) | 0.0 | |
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| DROP (3-shot) | 0.72 | |
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