Whisper-si-experiments
Collection
6 items • Updated
How to use SPEAK-ASR/whisper-si-exp-2 with PEFT:
from peft import PeftModel
from transformers import AutoModelForSeq2SeqLM
base_model = AutoModelForSeq2SeqLM.from_pretrained("pranay-j/whisper-small-hindi")
model = PeftModel.from_pretrained(base_model, "SPEAK-ASR/whisper-si-exp-2")How to use SPEAK-ASR/whisper-si-exp-2 with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("SPEAK-ASR/whisper-si-exp-2", dtype="auto")This model is a fine-tuned version of pranay-j/whisper-small-hindi on the Whisper Small - Sinhala ASR Fine-Tuned dataset. It achieves the following results on the evaluation set:
pranay-j/whisper-small-hindi as base modelSPEAK-ASR/speak-whisper-small-si-base-model-hindiMore information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5170 | 0.6527 | 500 | 0.5038 |
| 0.2936 | 1.3055 | 1000 | 0.2888 |
| 0.2858 | 1.9582 | 1500 | 0.2368 |
| 0.2248 | 2.6110 | 2000 | 0.2242 |
Base model
pranay-j/whisper-small-hindi