Transformers course UU - Spotify valence regression
Collection
Finetuned models and song datasets • 11 items • Updated
How to use EvelienUU/deberta-valence-lyrics-title_training2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="EvelienUU/deberta-valence-lyrics-title_training2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("EvelienUU/deberta-valence-lyrics-title_training2")
model = AutoModelForSequenceClassification.from_pretrained("EvelienUU/deberta-valence-lyrics-title_training2")This model is a fine-tuned version of EvelienUU/deberta-valence-lyrics-title_training1 on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Mae | Rmse | R Squared |
|---|---|---|---|---|---|---|
| 0.0483 | 0.32 | 1000 | 0.0503 | 0.1864 | 0.2242 | 0.2046 |
| 0.0476 | 0.64 | 2000 | 0.0471 | 0.1805 | 0.217 | 0.2549 |
| 0.0489 | 0.96 | 3000 | 0.0463 | 0.1763 | 0.2151 | 0.2679 |
| 0.0430 | 1.28 | 4000 | 0.0471 | 0.1769 | 0.2169 | 0.2554 |
| 0.0419 | 1.6 | 5000 | 0.0488 | 0.1803 | 0.221 | 0.2275 |
| 0.0424 | 1.92 | 6000 | 0.0472 | 0.1767 | 0.2173 | 0.2533 |
Base model
microsoft/deberta-v3-small