mt5-small-finetuned-genius
This model is a fine-tuned version of google/mt5-small on the Genius Music dataset found here. The song lyrics and song titles were preprocessed and used for fine-tuning.
You can view more examples of this model's inference on the following Space.
Model description
Please visit: google/mt5-small
Intended uses & limitations
- Intended Uses: Given song lyrics, generate a summary.
- Limitations: Due to the nature of music, the model can generate summaries containing hate speech.
Training and evaluation data
- 27.6K Training Samples
- 3.45 Validation Samples
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 7.9304 | 1.0 | 863 | 3.5226 | 14.235 | 6.78 | 14.206 | 14.168 |
| 3.8394 | 2.0 | 1726 | 3.0382 | 22.97 | 13.166 | 22.981 | 22.944 |
| 3.3799 | 3.0 | 2589 | 2.9010 | 24.932 | 14.54 | 24.929 | 24.919 |
| 3.2204 | 4.0 | 3452 | 2.8441 | 26.678 | 15.587 | 26.624 | 26.665 |
| 3.1498 | 5.0 | 4315 | 2.8363 | 26.827 | 15.696 | 26.773 | 26.793 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.1
- Tokenizers 0.13.3
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