---
language:
- en
license: mit
library_name: transformers
datasets:
- fedora-copr/autoannotated_snippets_mistral
metrics:
- rouge
tags:
- code
model_index:
  name: phi-2-snippets-logdetective
  results:
  - task:
      type: text-generation
    dataset:
      type: fedora-copr/autoannotated_snippets_mistral
      name: autoannotated_snippets_mistral
    metrics:
      - name: rouge-1-recall
        type: rouge-1
        value: 0.4928060294187831
        verified: false
      - name: rouge-1-precision
        type: rouge-1
        value: 0.3842279864863966
        verified: false
      - name: rouge-1-f1
        type: rouge-1
        value: 0.4228375247665276
        verified: false
      - name: rouge-2-recall
        type: rouge-2
        value: 0.22104701377745636
        verified: false
      - name: rouge-2-precision
        type: rouge-2
        value: 0.15216741180621804
        verified: false
      - name: rouge-2-f1
        type: rouge-2
        value: 0.17506785950227427
        verified: false
      - name: rouge-l-recall
        type: rouge-l
        value: 0.4588693388086414
        verified: false
      - name: rouge-l-precision
        type: rouge-l
        value: 0.3579633500466938
        verified: false
      - name: rouge-l-f1
        type: rouge-l
        value: 0.3938760006165079
        verified: false
---

# Model Card for Model ID

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## Model Details

### Model Description

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- **Developed by:** Jiri Podivin <jpodivin@redhat.com>
- **Model type:** phi-2
- **Language(s) (NLP):** English
- **License:** MIT
- **Finetuned from model [optional]:** microsoft/phi-2


### Model Sources [optional]

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

## Uses

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### Direct Use

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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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[More Information Needed]

### 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

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### Testing Data, Factors & Metrics

#### Testing Data

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[fedora-copr/autoannotated_snippets_mistral](https://huggingface.co/datasets/fedora-copr/autoannotated_snippets_mistral)

#### Factors

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[More Information Needed]

#### Metrics

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Rouge metric was used to compare model outputs with expected annotations from test subset.

### Results

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#### Summary

## Technical Specifications

### Compute Infrastructure

Single node

#### Hardware

- 1 * GeForce RTX 4090

#### Software

- transformers
- peft

## Model Card Authors [optional]

- Jiri Podivin <jpodivin@redhat.com>