Transformers course UU - Spotify valence regression
Collection
Finetuned models and song datasets • 11 items • Updated
How to use EvelienUU/deberta-valence-title_training2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="EvelienUU/deberta-valence-title_training2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("EvelienUU/deberta-valence-title_training2")
model = AutoModelForSequenceClassification.from_pretrained("EvelienUU/deberta-valence-title_training2")This model is a fine-tuned version of EvelienUU/deberta-valence-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 |
|---|---|---|---|---|---|---|
| 0.0592 | 0.32 | 1000 | 0.0569 | 0.1994 | 0.2386 | 0.0996 |
| 0.0558 | 0.64 | 2000 | 0.0584 | 0.2011 | 0.2417 | 0.0755 |
| 0.0590 | 0.96 | 3000 | 0.0570 | 0.199 | 0.2388 | 0.0982 |
| 0.0557 | 1.28 | 4000 | 0.0579 | 0.1986 | 0.2406 | 0.0845 |
| 0.0533 | 1.6 | 5000 | 0.0567 | 0.1975 | 0.2381 | 0.1033 |
| 0.0550 | 1.92 | 6000 | 0.0567 | 0.1973 | 0.2382 | 0.1025 |
Base model
microsoft/deberta-v3-small