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2. [Uses](#uses)
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3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
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4. [Training Details](#training-details)
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5. [Evaluation](#evaluation)
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6. [Model Examination](#model-examination-optional)
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7. [Environmental Impact](#environmental-impact)
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8. [Technical Specifications](#technical-specifications-optional)
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9. [Citation](#citation-optional)
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10. [Glossary](#glossary-optional)
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11. [More Information](#more-information-optional)
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12. [Model Card Authors](#model-card-authors-optional)
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13. [Model Card Contact](#model-card-contact)
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14. [How To Get Started With the Model](#how-to-get-started-with-the-model)
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** en
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- **License:** mit
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- **Finetuned from model [optional]:** [More Information Needed]
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- **Resources for more information:** [More Information Needed]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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## Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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# Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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## Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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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# Training Details
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## Training Data
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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## Training Procedure [optional]
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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### Preprocessing
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[More Information Needed]
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### Speeds, Sizes, Times
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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# Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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## Testing Data, Factors & Metrics
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### Testing Data
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<!-- This should link to a Data Card if possible. -->
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[More Information Needed]
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### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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## Results
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[More Information Needed]
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# Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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# Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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# Technical Specifications [optional]
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## Model Architecture and Objective
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[More Information Needed]
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## Compute Infrastructure
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[More Information Needed]
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### Hardware
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[More Information Needed]
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### Software
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[More Information Needed]
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# Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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# Glossary [optional]
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<!-- 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 Needed]
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# More Information [optional]
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[More Information Needed]
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# Model Card Authors [optional]
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[More Information Needed]
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# Model Card Contact
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[More Information Needed]
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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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<details>
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<summary> Click to expand </summary>
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[More Information Needed]
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</details>
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value: 15.134827404979639
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# BARTxiv
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the [arxiv-summarization](https://huggingface.co/datasets/ccdv/arxiv-summarization) dataset.
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It achieves the following results on the validation set:
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- Loss: 0.86
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- Rouge1: 41.70
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- Rouge2: 15.13
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- Rougel: 22.85
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- Rougelsum: 37.77
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-6
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- optimizer: Adafactor
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- num_epochs: 9
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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| 1.24 | 1.0 | 1073 | 7.8495 | 38.32 | 12.80 | 20.55 | 34.50 |
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| 1.04 | 2.0 | 2146 | 5.8341 | 39.65 | 13.74 | 21.28 | 35.83 |
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| 0.979 | 3.0 | 3219 | 4.0960 | 40.19 | 14.30 | 21.87 | 36.38 |
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| 0.970 | 4.0 | 4292 | 3.5401 | 40.87 | 14.44 | 22.14 | 36.89 |
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| 0.918 | 5.0 | 5365 | 3.5401 | 41.17 | 14.94 | 22.54 | 37.40 |
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| 0.901 | 6.0 | 6438 | 3.5401 | 41.02 | 14.65 | 22.46 | 37.05 |
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| 0.889 | 7.0 | 7511 | 3.5401 | 41.32 | 15.09 | 22.64 | 37.42 |
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| 0.900 | 8.0 | 8584 | 3.5401 | 41.23 | 15.02 | 22.67 | 37.28 |
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| 0.869 | 9.0 | 9657 | 3.5401 | 41.70 | 15.13 | 22.85 | 37.77 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu117
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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