poemma / README.md
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---
library_name: transformers
tags:
- poetry
- qlora
- merged
model-index:
- name: prettyvampire/poemma
results:
- task:
type: text-generation
name: Poems Annotation Generation
dataset:
name: Genius Poems Annotations
type: prettyvampire/genius_poems_annotations
split: test
metrics:
- type: rouge
value: 0.185
name: ROUGE1
- type: bleu
value: 0.005
name: BLEU
- type: bertscore
value: 0.826
name: BERTscore Mean Precision
- type: bertscore
value: 0.846
name: BERTscore Mean Recall
- type: bertscore
value: 0.836
name: BERTscore Mean F1
- type: bleurt
value: -0.926
name: BLEURT Mean
license: apache-2.0
datasets:
- prettyvampire/genius_poems_annotations
language:
- en
metrics:
- bertscore
- bleu
- rouge
- bleurt
base_model:
- meta-llama/Llama-3.2-3B-Instruct
pipeline_tag: text-generation
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
Large Language model for interpretation of poetry.
**Input example:**
You are given the poem "Song of Beren and Lúthien" by J. R. R. Tolkien.
<poem>
One moment stood she, and a spell
His voice laid on her: Beren came,
And doom fell on Tinúviel
That in his arms lay glistening.
As Beren looked into her eyes
Within the shadows of her hair,
The trembling starlight of the skies
He saw there mirrored shimmering.
Tinúviel the elven-fair,
Immortal maiden elven-wise,
About him cast her shadowy hair
And arms like silver glimmering.
Long was the way that fate them bore,
O'er stony mountains cold and grey,
Through halls of iron and darkling door,
And woods of nightshade morrowless.
</poem>
Explain the meaning of the following lines: "Long was the way that fate them bore,"
**Output example:**
The fate of the two lovers is a long and difficult one, as we have already seen. Beren and Luthien are to be separated and are forced to travel far and wide. Their journey is a long one and is filled with danger and hardship. The fate that is laid upon them is one that they cannot escape.
This is a reference to the story of Orpheus and Eurydice, which is another love story that is filled with hardship and tragedy. Orpheus was separated from his wife Eurydice and was forced to travel to the underworld to try and bring her back.
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Language(s) (NLP):** English
- **Finetuned from model [optional]:** meta-llama/Llama-3.1-8B-Instruct
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed] https://github.com/lovelyscientist/poemma
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
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[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[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.
[More Information Needed]
## Training Details
### Training Data
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[More Information Needed]
### Training Procedure
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#### Preprocessing [optional]
[More Information Needed]
#### 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]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
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[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
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#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
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**APA:**
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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