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Model: pszemraj/pythia-31m-goodwiki-deduped-2048-scratch Source: Original Platform
2026-04-21 07:15:55 +08:00
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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+inference:
+  parameters:
+    max_new_tokens: 64
+    do_sample: true
+    repetition_penalty: 1.1
+    no_repeat_ngram_size: 5
+    guidance_scale: 1.01
+    eta_cutoff: 0.001
+widget:
+- text: My name is El Microondas the Wise and
+  example_title: El Microondas
+- text: A meme is
+  example_title: meme
+- text: >-
+    Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
+    He chose her because she had
+  example_title: Coreference resolution
+- text: >-
+    On a shelf, there are five books: a gray book, a red book, a purple book, a
+    blue book, and a black book
+  example_title: Logic puzzles
+- text: >-
+    The two men running to become New York City's next mayor will face off in
+    their first debate Wednesday night
+  example_title: Reading comprehension
+pipeline_tag: text-generation
+license: apache-2.0
+datasets:
+- euirim/goodwiki
+language:
+- en
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# pythia-31m-goodwiki-deduped-2048-scratch
+
+Train from scratch based on config of [EleutherAI/pythia-31m](https://huggingface.co/EleutherAI/pythia-31m) for 3 epochs.
+
+It achieves the following results on the evaluation set:
+- Loss: 4.5181
+- Accuracy: 0.2680
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+```
+***** eval metrics *****                                              
+  epoch                   =        3.0                   
+  eval_accuracy           =     0.2694                                  eval_loss               =     4.4986                                
+  eval_runtime            = 0:00:14.62                                
+  eval_samples            =        500                                  eval_samples_per_second =     34.187                                  eval_steps_per_second   =     17.093                              
+  perplexity              =    89.8934
+```
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0005
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 80085
+- gradient_accumulation_steps: 64
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
+- lr_scheduler_type: inverse_sqrt
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 6.8347        | 0.16  | 100  | 6.7683          | 0.1380   |
+| 6.0732        | 0.32  | 200  | 6.0489          | 0.1712   |
+| 5.6949        | 0.48  | 300  | 5.6941          | 0.1935   |
+| 5.4723        | 0.64  | 400  | 5.4411          | 0.2066   |
+| 5.2672        | 0.8   | 500  | 5.2621          | 0.2162   |
+| 5.165         | 0.96  | 600  | 5.1339          | 0.2241   |
+| 5.0693        | 1.12  | 700  | 5.0290          | 0.2304   |
+| 4.9234        | 1.28  | 800  | 4.9430          | 0.2369   |
+| 4.886         | 1.44  | 900  | 4.8702          | 0.2413   |
+| 4.8422        | 1.6   | 1000 | 4.8086          | 0.2458   |
+| 4.7688        | 1.76  | 1100 | 4.7593          | 0.2488   |
+| 4.734         | 1.93  | 1200 | 4.7118          | 0.2527   |
+| 4.6877        | 2.09  | 1300 | 4.6721          | 0.2556   |
+| 4.6135        | 2.25  | 1400 | 4.6350          | 0.2583   |
+| 4.6117        | 2.41  | 1500 | 4.6013          | 0.2606   |
+| 4.5424        | 2.57  | 1600 | 4.5707          | 0.2635   |
+| 4.5535        | 2.73  | 1700 | 4.5447          | 0.2658   |
+| 4.4823        | 2.89  | 1800 | 4.5181          | 0.2680   |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.2.0.dev20230907+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 24.85   |
+| ARC (25-shot)         | 23.12          |
+| HellaSwag (10-shot)   | 25.66    |
+| MMLU (5-shot)         | 23.11         |
+| TruthfulQA (0-shot)   | 51.32   |
+| Winogrande (5-shot)   | 49.88   |
+| GSM8K (5-shot)        | 0.0        |
+| DROP (3-shot)         | 0.86         |