metadata
language:
- en
tags:
- pytorch
- text-generation
- causal-lm
- rwkv
license: apache-2.0
datasets:
- the_pile
RWKV-4 430M
Use RWKV-4 models (NOT RWKV-4a, NOT RWKV-4b) unless you know what you are doing.
Use RWKV-4 models (NOT RWKV-4a, NOT RWKV-4b) unless you know what you are doing.
Use RWKV-4 models (NOT RWKV-4a, NOT RWKV-4b) unless you know what you are doing.
Model Description
RWKV-4 430M is a L24-D1024 causal language model trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.
Use https://github.com/BlinkDL/ChatRWKV to run it.
ctx_len = 1024 n_layer = 24 n_embd = 1024
Final checkpoint: RWKV-4-Pile-430M-20220808-8066.pth : Trained on the Pile for 333B tokens.
- Pile loss 2.2621
- LAMBADA ppl 13.04, acc 45.16%
- PIQA acc 67.52%
- SC2016 acc 63.87%
- Hellaswag acc_norm 40.90%
With tiny attention (--tiny_att_dim 512 --tiny_att_layer 18): RWKV-4a-Pile-433M-20221223-8039.pth
- Pile loss 2.2394
- LAMBADA ppl 10.54, acc 50.20%
- PIQA acc 68.12%
- SC2016 acc 63.55%
- Hellaswag acc_norm 40.82%
RWKV-4b-Pile-436M-20230211-8012.pth (--my_testing 'a')
- Pile loss 2.2026
- LAMBADA ppl 10.48, acc 51.35%
- PIQA acc 68.06%
- SC2016 acc 63.17%
- Hellaswag acc_norm 42.09%