File size: 3,107 Bytes
9db4394 b7c077c 72d8dc9 ff37e0f 72d8dc9 b7c077c 47255fc b7c077c 47255fc 9df5712 d23a266 9df5712 8cb59a0 0265c12 8cb59a0 0265c12 243c3a4 8cb59a0 0265c12 8cb59a0 787df88 30390ad 787df88 30390ad 8cb59a0 243c3a4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
license: openrail
---
Experimental Tagalog loras: safe or accurate outputs not guaranteed (not for production use)!
Note: better/best results with
* Prompting in Tagalog
* Using format "Human: (prompt)\nAssistant:"
Example:
"Ito ay isang chat log sa pagitan ng AI Assistant na nagta-Tagalog at isang Pilipino. Magsimula ng chat:\nHuman: Hello po?\nAssistant:"
# lt2_08162023
* Fine tuned on a small dataset of 14 items, manually edited
* 1 epoch (barely any noticable results)
* From chat LLaMA-2-7b
* Lora of chat-tagalog v0.1
# lt2_08162023a
* Fine tuned on a small dataset of 14 items, manually edited
* 20 epochs (more observable effects)
* From chat LLaMA-2-7b
* Lora of [chat-tagalog v0.1a](https://huggingface.co/922-Narra/llama-2-7b-chat-tagalog-v0.1a)
# lt2_08162023b
* Fine tuned on a small dataset of 14 items, manually edited
* 10 epochs
* From chat LLaMA-2-7b
* Lora of chat-tagalog v0.1b
# lt2_08162023c
* Fine tuned on a small dataset of 14 items, manually edited
* 50 epochs (overfitted)
* From chat LLaMA-2-7b
* Lora of chat-tagalog v0.1c
# lt2_08162023d
* Fine tuned on a small dataset of 14 items, manually edited
* 30 epochs (v0.1a further trained and cut-off before overfit)
* From chat LLaMA-2-7b
* Lora of [chat-tagalog v0.1d](https://huggingface.co/922-Narra/llama-2-7b-chat-tagalog-v0.1d)
# llama-2-7b-tagalog-v0.2 loras (08/26/2023)
* Fine tuned on dataset of ~10k items (mixed)
* 2/2a/2b fine-tuned for 1/2/3 epochs
* From chat LLaMA-2-7b
* Future attempt planned with cleaner chat/dialogue data
# hopia-3b-v0.1 (08/26/2023)
* Fine tuned on a small dataset of 14 items, manually edited
* 20 epochs
* From Open LLaMA 3b
# llama-2-7b-tagalog-v0.3 loras (09/01/2023)
* Fine tuned on a dataset of ~1k items (Tagalog-focused dataset, based off Tagalog sentences augmented by LLaMA-2-13b base to create a 3-turn dialogue dataset between Human and Assistant)
* 3/3a fine-tuned for 1/2 epochs
* From chat LLaMA-2-7b
* Experiment on partially synthetic data (and observing capability of LLaMA-2 base on generating Tagalog): will be further curating dataset
* Loras for [chat-tagalog v0.3)](https://huggingface.co/922-Narra/llama-2-7b-chat-tagalog-v0.3) and [chat-tagalog v0.3](https://huggingface.co/922-Narra/llama-2-7b-chat-tagalog-v0.3a)
# llama-2-7b-tagalog-v0.3WC2 (09/01/2023)
* Fine tuned on experimental dataset of ~6k items (Tagalog-focused dataset, based off Tagalog sentences and Wiki entries augmented by LLaMA-2-13b to create a dialogue-QnA dataset between Human and Assistant)
* 1 epoch
* From chat LLaMA-2-7b
# llama-2-13b-tagalog-v0.3 loras (09/01-02/2023)
* Fine tuned on experimental datasets of ~1k items (Tagalog-focused dataset, based off Tagalog sentences augmented by LLaMA-2-13b base to create a 3-turn dialogue dataset between Human and Assistant)
* 3 fine-tuned for 1 epoch, rank = 16, lora alpha = 32
* 3a with rank = 8
* 3b for 2 epochs
* 3c for 1 epoch, lr = 1e-4, warmup steps = 0.1
* 3d with lr = 2e-4, rank = 32, lora alpha = 64
* 3e for 2 epochs
* From LLaMA-2-13b
* Trying LLaMA-2-13b chat/other base and curated dataset for next attempts |