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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- summarization |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-genius |
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results: [] |
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pipeline_tag: summarization |
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datasets: |
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- miscjose/genius |
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--- |
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# mt5-small-finetuned-genius |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the [Genius](https://genius.com/) Music dataset found [here](https://www.cs.cornell.edu/~arb/data/genius-expertise/). |
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The song lyrics and song titles were preprocessed and used for fine-tuning. |
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You can view more examples of this model's inference on the following [Space](https://huggingface.co/spaces/miscjose/genius_summarization_space) |
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## Model description |
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Please visit: [google/mt5-small](https://huggingface.co/google/mt5-small) |
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## Intended uses & limitations |
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- Intended Uses: Given song lyrics, generate a summary. |
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- Limitations: Due to the nature of music, the model can generate summaries containing hate speech. |
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## Training and evaluation data |
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- 27.6K Training Samples |
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- 3.45 Validation Samples |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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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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| 7.9304 | 1.0 | 863 | 3.5226 | 14.235 | 6.78 | 14.206 | 14.168 | |
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| 3.8394 | 2.0 | 1726 | 3.0382 | 22.97 | 13.166 | 22.981 | 22.944 | |
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| 3.3799 | 3.0 | 2589 | 2.9010 | 24.932 | 14.54 | 24.929 | 24.919 | |
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| 3.2204 | 4.0 | 3452 | 2.8441 | 26.678 | 15.587 | 26.624 | 26.665 | |
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| 3.1498 | 5.0 | 4315 | 2.8363 | **26.827** | **15.696** | **26.773** | **26.793** | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
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