---
library_name: transformers
tags:
- merge
- sliced
- minimalist
license: apache-2.0
metrics:
- accuracy
- bleu
---

# Model Card for Model ID

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## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** Tatman Electric
- **Funded by [optional]:** Spare Pocket Lint
- **Shared by [optional]:** TRL
- **Model type:** Sliced Layered
- **Language(s) (NLP):** Mixed
- **License:** Pythia @ EleutherAI
- **Finetuned from model [optional]:** EleutherAI/pythia-2.8b-deduped

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

Before there were merged models, there were slices of shards of... stuff. Those slices have meaning. Those slices are real slices too.

### Direct Use
Part of a series of slice and dice mods.

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##### Single Hidden Layer Pythia
What does a single hidden layer preserve from a 12 layer base model?

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

|       Groups       |Version|     Filter     |n-shot|  Metric   | Value |   |Stderr|
|--------------------|-------|----------------|-----:|-----------|------:|---|-----:|
|Open LLM Leaderboard|N/A    |none            |     5|rouge1_max |36.3550|±  |0.9462|
|                    |       |flexible-extract|     5|exact_match| 0.0220|±  |0.0066|
| - arc_challenge    |      1|none            |    25|acc        | 0.1760|±  |0.0170|
|                    |       |none            |    25|acc_norm   | 0.2320|±  |0.0189|
| - gsm8k            |      3|strict-match    |     5|exact_match| 0.0060|±  |0.0035|
|                    |       |flexible-extract|     5|exact_match| 0.0220|±  |0.0066|
| - hellaswag        |      1|none            |    10|acc        | 0.3520|±  |0.0214|
|                    |       |none            |    10|acc_norm   | 0.4040|±  |0.0220|
| - winogrande       |      1|none            |     5|acc        | 0.5120|±  |0.0224|
|                    |       |none            |     5|bleu_diff  |-0.6500|±  |0.6421|
|                    |       |none            |     5|rouge1_acc | 0.3700|±  |0.0216|
|                    |       |none            |     5|rouge1_diff|-1.5564|±  |1.0223|
|                    |       |none            |     5|acc        | 0.2664|±  |0.0036|
|                    |       |none            |     5|rougeL_max |33.8798|±  |0.9367|
|                    |       |none            |     5|rouge2_diff|-3.3178|±  |0.9477|
|                    |       |none            |     5|bleu_max   |15.2292|±  |0.6714|
|                    |       |none            |     5|bleu_acc   | 0.4360|±  |0.0222|
|                    |       |none            |     5|rouge2_max |16.4873|±  |1.0172|
|                    |       |none            |     5|acc_norm   | 0.3180|±  |0.0145|
|                    |       |strict-match    |     5|exact_match| 0.0060|±  |0.0035|
|                    |       |none            |     5|rougeL_diff|-0.7765|±  |1.0034|
|                    |       |none            |     5|rougeL_acc | 0.3860|±  |0.0218|
|                    |       |none            |     5|rouge2_acc | 0.1920|±  |0.0176|
| - mmlu             |N/A    |none            |     0|acc        | 0.2533|±  |0.0039|
|  - humanities      |N/A    |none            |     5|acc        | 0.2408|±  |0.0075|
|  - other           |N/A    |none            |     5|acc        | 0.2443|±  |0.0080|
|  - social_sciences |N/A    |none            |     5|acc        | 0.2538|±  |0.0081|
|  - stem            |N/A    |none            |     5|acc        | 0.2740|±  |0.0079|
| - truthfulqa       |N/A    |none            |     0|rouge1_max |36.3550|±  |0.9462|
|                    |       |none            |     0|bleu_diff  |-0.6500|±  |0.6421|
|                    |       |none            |     0|rouge1_acc | 0.3700|±  |0.0216|
|                    |       |none            |     0|rouge1_diff|-1.5564|±  |1.0223|
|                    |       |none            |     0|acc        | 0.3435|±  |0.0137|
|                    |       |none            |     0|rougeL_max |33.8798|±  |0.9367|
|                    |       |none            |     0|bleu_max   |15.2292|±  |0.6714|
|                    |       |none            |     0|bleu_acc   | 0.4360|±  |0.0222|
|                    |       |none            |     0|rouge2_max |16.4873|±  |1.0172|
|                    |       |none            |     0|rougeL_acc | 0.3860|±  |0.0218|
|                    |       |none            |     0|rougeL_diff|-0.7765|±  |1.0034|
|                    |       |none            |     0|rouge2_acc | 0.1920|±  |0.0176|
|                    |       |none            |     0|rouge2_diff|-3.3178|±  |0.9477|

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** OldAsDirt
- **Hours used:** 5
- **Cloud Provider:** YourMomsBasement
- **Compute Region:** Siberia
- **Carbon Emitted:** 8ppm
  
No yaks were harmed in the making of this model.

## Technical Specifications [optional]

### Model Architecture and Objective

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## Citation [optional]

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## Glossary [optional]

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## Model Card Authors [optional]

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