SPEAK-PP/akura-sinhala-dyslexia-corrected
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How to use SPEAK-PP/mt5-base-si with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("SPEAK-PP/mt5-base-si")
model = AutoModelForSeq2SeqLM.from_pretrained("SPEAK-PP/mt5-base-si")This model is a fine-tuned version of google/mt5-base on the SPEAK-ASR/akura-sinhala-dyslexia-corrected 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 |
|---|---|---|---|
| 0.9075 | 0.9921 | 500 | 0.6071 |
| 0.3976 | 1.9841 | 1000 | 0.1844 |
| 0.0881 | 2.9762 | 1500 | 0.0740 |
| 0.2419 | 3.9683 | 2000 | 0.0734 |
| 0.1458 | 4.9603 | 2500 | 0.0735 |
Base model
google/mt5-base