transformers safetensors gpt_neox text-generation autotrain_compatible text-generation-inference endpoints_compatible 4-bit bitsandbytes region:us
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Quantization made by Richard Erkhov.

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pythia-31m-goodwiki-deduped-2048-scratch - bnb 4bits
- Model creator: https://huggingface.co/pszemraj/
- Original model: https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch/




Original model description:
---
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         |


