metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
- music
- song-lyrics
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-genius
results: []
pipeline_tag: summarization
datasets:
- miscjose/genius-music
widget:
- text: >
Thought I'd end up with Sean But he wasn't a match Wrote some songs
about Ricky Now I listen and laugh Even almost got married And for Pete,
I'm so thankful Wish I could say, "Thank you" to Malcolm 'Cause he was an
angel One taught me love One taught me patience And one taught me pain
Now, I'm so amazing Say I've loved and I've lost But that's not what I see
So, look what I got Look what you taught me And for that, I say Thank you,
next (Next) Thank you, next (Next) Thank you, next I'm so fuckin' grateful
for my ex Thank you, next (Next) Thank you, next (Next) Thank you, next
(Next) I'm so fuckin'— Spend more time with my friends I ain't worried
'bout nothin' Plus, I met someone else We havin' better discussions I know
they say I move on too fast But this one gon' last 'Cause her name is Ari
And I'm so good with that (So good with that) She taught me love (Love)
She taught me patience (Patience) How she handles pain (Pain) That shit's
amazing (Yeah, she's amazing) I've loved and I've lost (Yeah, yeah) But
that's not what I see (Yeah, yeah) 'Cause look what I've found (Yeah,
yeah, I've found) Ain't no need for searching, and for that, I say Thank
you, next (Thank you, next) Thank you, next (Thank you, next) Thank you,
next (Thank you) I'm so fuckin' grateful for my ex Thank you, next (Thank
you, next) Thank you, next (Said thank you, next) Thank you, next (Next)
I'm so fuckin' grateful for my ex Thank you, next Thank you, next Thank
you, next I'm so fuckin'— One day I'll walk down the aisle Holding hands
with my mama I'll be thanking my dad 'Cause she grew from the drama Only
wanna do it once, real bad Gon' make that shit last God forbid something
happens Least this song is a smash (Song is a smash) I've got so much love
(Love) Got so much patience (Patience) And I've learned from the pain
(Pain) I turned out amazing (Turned out amazing) Say I've loved and I've
lost (Yeah, yeah) But that's not what I see (Yeah, yeah) 'Cause look what
I've found (Yeah, yeah) Ain't no need for searching And for that, I say
Thank you, next (Thank you, next) Thank you, next (Thank you, next) Thank
you, next I'm so fuckin' grateful for my ex Thank you, next (Thank you,
next) Thank you, next (Said thank you, next) Thank you, next (Next) I'm so
fuckin' grateful for my ex Thank you, next Thank you, next Thank you, next
Yeah, yee Thank you, next Thank you, next Thank you, next Yeah, yee
- text: |
I thought as much Test Test
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