readme: ---
  language:
  - en
  tags:
  - pytorch
  - text-generation
  - causal-lm
  - rwkv
  license: apache-2.0
  datasets:
  - the_pile
  
  ---
  
  # RWKV-4 1.5B
  
  ## Model Description
  
  RWKV-4 1.5B is a L24-D2048 causal language model trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.
  
  ** Note: It's a BF16 model, and it may overflow if you are using FP16 (probably fixable by rescaling the weights). **
  
  At this moment you have to use my Github code (https://github.com/BlinkDL/RWKV-LM) to run it.
  
  ctx_len = 1024
  n_layer = 24
  n_embd = 2048
  
  New checkpoint: RWKV-4-Pile-1B5-20220929-ctx4096.pth : Fine-tuned to ctx_len = 4096
  
  Final checkpoint: RWKV-4-Pile-1B5-20220903-8040.pth : Trained on the Pile for 332B tokens.
  * Pile loss 2.0415
  * LAMBADA ppl 7.04, acc 56.43%
  * PIQA acc 72.36%
  * SC2016 acc 68.73%
  * Hellaswag acc_norm 52.48%
  
  Preview checkpoint: RWKV-4-Pile-1B5-20220822-5809.pth : Trained on the Pile for 240B tokens.
  * Pile loss 2.0518
  * LAMBADA ppl 7.14, acc 56.36%
  * PIQA acc 71.71%
  * SC2016 acc 68.15%
  * Hellaswag acc_norm 52.04%
  
  Preview checkpoint: RWKV-4-Pile-1B5-20220814-4526.pth : Trained on the Pile for 187B tokens.
  * Pile loss 2.0635
  * LAMBADA ppl 7.34, acc 55.64%
  * PIQA acc 71.44%
  * SC2016 acc 68.25%
  * Hellaswag acc_norm 51.60%
  
  ## Warning: 4 / 4a / 4b models ARE NOT compatible!!! Use RWKV-4 unless you know what you are doing.
  