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  9B rocm-rwkv pth record: 40 layers embd=4096 ctx= 16384 I am calling this model Quetzal. I called this model Quetzal since it is a green model that flies and I am adding an extra training focusing on Spanish and the dataset Axolotl-Spanish-Nahuatl after each run.
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  - rwkv-9Q-stp101-N8.pth: 9B rocm-rwkv model trained with Slim pajama chunk1-10 for the first epoch and an aditional training with chunk1-2 and a mix of multi-language and code after that I am using the N8 dataset. I am currendly with the N8 dataset 4.222 GTokes. This pth has a loss of 1.904 regarding the N8 dataset.
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- - rwkv-9Q-stp101-N8.pth: 9B rocm-rwkv model trained with Slim pajama chunk1-10 for the first epoch and an aditional training with chunk1-2 and a mix of multi-language and code after that I am using the N8 dataset. I am currendly with the N8 dataset 12.706 GTokes. This pth has a loss of 1.871 regarding the N8 dataset.
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  9B rocm-rwkv pth record: 40 layers embd=4096 ctx= 16384 I am calling this model Quetzal. I called this model Quetzal since it is a green model that flies and I am adding an extra training focusing on Spanish and the dataset Axolotl-Spanish-Nahuatl after each run.
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  - rwkv-9Q-stp101-N8.pth: 9B rocm-rwkv model trained with Slim pajama chunk1-10 for the first epoch and an aditional training with chunk1-2 and a mix of multi-language and code after that I am using the N8 dataset. I am currendly with the N8 dataset 4.222 GTokes. This pth has a loss of 1.904 regarding the N8 dataset.
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+ - rwkv-9Q-1k-stp307-1k-N8.pth: 9B rocm-rwkv model trained with Slim pajama chunk1-10 for the first epoch and an aditional training with chunk1-2 and a mix of multi-language and code after that I am using the N8 dataset. I am currendly with the N8 dataset 12.706 GTokes. This pth has a loss of 1.871 regarding the N8 dataset.
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