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