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--- |
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library_name: transformers |
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license: llama3.1 |
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datasets: |
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- HoangHa/Pensez |
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language: |
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- en |
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- fr |
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--- |
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# Results |
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lm harness with French bench |
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| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |
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|-------------------------------|-------|------|-----:|-----------|---|-----:|---|------| |
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|french_bench_arc_challenge |Yaml |none | 5|acc |↑ |0.4482|± |0.0146| |
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| | |none | 5|acc_norm |↑ |0.4816|± |0.0146| |
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|french_bench_boolqa |Yaml |none | 5|acc |↑ |0.8371|± |0.0278| |
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| | |none | 5|acc_norm |↑ |0.8371|± |0.0278| |
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|french_bench_fquadv2 |Yaml |none | 5|exact |↑ |0.3100|± |0.0164| |
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| | |none | 5|f1 |↑ |0.4392|± |0.0161| |
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|french_bench_fquadv2_bool |Yaml |none | 5|acc |↑ |0.7462|± |0.0154| |
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| | |none | 5|acc_norm |↑ |0.7462|± |0.0154| |
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|french_bench_fquadv2_genq |Yaml |none | 5|f1 |↑ |0.3451|± |0.0113| |
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| | |none | 5|rouge1 |↑ |0.3746|± | N/A| |
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|french_bench_fquadv2_hasAns |Yaml |none | 5|exact |↑ |0.5300|± |0.0250| |
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| | |none | 5|f1 |↑ |0.7827|± |0.0154| |
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| | |none | 5|rouge1 |↑ |0.7889|± | N/A| |
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|french_bench_grammar |Yaml |none | 5|acc |↑ |0.7647|± |0.0390| |
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|french_bench_hellaswag |Yaml |none | 5|acc |↑ |0.4900|± |0.0052| |
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| | |none | 5|acc_norm |↑ |0.6423|± |0.0050| |
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|french_bench_multifquad |Yaml |none | 5|exact |↑ |0.2000|± |0.0200| |
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| | |none | 5|f1 |↑ |0.6739|± |0.0141| |
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| | |none | 5|rouge1 |↑ |0.6822|± | N/A| |
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|french_bench_orangesum_abstract|Yaml |none | 5|rouge1 |↑ |0.3021|± | N/A| |
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|french_bench_orangesum_title |Yaml |none | 5|rouge1 |↑ |0.3716|± | N/A| |
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|french_bench_reading_comp |Yaml |none | 5|acc |↑ |0.6620|± |0.0565| |
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|french_bench_topic_based_nli |Yaml |none | 5|acc |↑ |0.6767|± |0.0191| |
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| | |none | 5|acc_norm |↑ |0.6767|± |0.0191| |
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|french_bench_trivia |Yaml |none | 5|exact |↑ |0.5421|± |0.0256| |
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| | |none | 5|f1 |↑ |0.6887|± |0.0205| |
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| | |none | 5|is_included|↑ |0.5684|± |0.0254| |
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| | |none | 5|rouge1 |↑ |0.6992|± | N/A| |
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|french_bench_vocab |Yaml |none | 5|acc |↑ |0.7731|± |0.0386| |
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|french_bench_xnli |Yaml |none | 5|acc |↑ |0.4529|± |0.0070| |
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# Model Card for Model ID |
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## Model Details |
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### 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. |
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- **Developed by:** [More Information Needed] |
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- **Language(s) (NLP):** [More Information Needed] |
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## Uses |
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### Direct Use |
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## Bias, Risks, and Limitations |
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[More Information Needed] |
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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. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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### Training Procedure |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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## Evaluation |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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[More Information Needed] |
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#### Factors |
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[More Information Needed] |
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#### Metrics |
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### Results |
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#### Summary |
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## 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). |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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### Compute Infrastructure |
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#### Hardware |
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#### Software |
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## Citation [optional] |
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**BibTeX:** |
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**APA:** |
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## More Information [optional] |
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