deliciouscat/deberta-v3-base-encoder-decoder-v0.2

Encoder-Decoder model with DeBERTa encoder

pre-trained models

• —Encoder: microsoft/deberta-v3-small

• —Decoder: deliciouscat/deberta-v3-base-decoder-v0.1 (6 transformer layers, 8 attention heads)

-> 297511524(298M) params

Data used

HuggingFaceFW/fineweb -> sampled 124800

Training hparams

• —optimizer: AdamW, lr=2.3e-5, betas=(0.875, 0.997)

• —batch size: 12 (maximal on Colab pro A100 env)

-> training on denoising objective (BART)

How to use

from transformers import AutoTokenizer, EncoderDecoderModel

model = EncoderDecoderModel.from_pretrained("deliciouscat/deberta-v3-base-encoder-decoder-v0.2")
tokenizer = AutoTokenizer.from_pretrained("deliciouscat/deberta-v3-base-encoder-decoder-v0.2")

Future work!

• —train more scientific data

• —fine-tune on keyword extraction task