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Update lora config

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NanoCode012
2023-05-25 17:26:39 +09:00
parent 8552218491
commit 9083910036
1 changed files with 7 additions and 2 deletions
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README.md
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@@ -134,7 +134,7 @@ See sample configs in [configs](configs) folder or [examples](examples) for quic
- lora - lora
```yaml ```yaml
adapter: lora # blank for full finetune adapter: lora # qlora or leave blank for full finetune
lora_r: 8 lora_r: 8
lora_alpha: 16 lora_alpha: 16
lora_dropout: 0.05 lora_dropout: 0.05
@@ -185,6 +185,8 @@ datasets:
# The type of prompt to use for training. [alpaca, sharegpt, gpteacher, oasst, reflection] # The type of prompt to use for training. [alpaca, sharegpt, gpteacher, oasst, reflection]
type: alpaca type: alpaca
data_files: # path to source data files data_files: # path to source data files
shards: # true if use subset data. make sure to set `shards` param also
shards: # number of shards to split dataset into
# axolotl attempts to save the dataset as an arrow after packing the data together so # axolotl attempts to save the dataset as an arrow after packing the data together so
# subsequent training attempts load faster, relative path # subsequent training attempts load faster, relative path
@@ -201,7 +203,7 @@ sequence_len: 2048
# inspired by StackLLaMA. see https://huggingface.co/blog/stackllama#supervised-fine-tuning # inspired by StackLLaMA. see https://huggingface.co/blog/stackllama#supervised-fine-tuning
max_packed_sequence_len: 1024 max_packed_sequence_len: 1024
# if you want to use lora, leave blank to train all parameters in original model # if you want to use 'lora' or 'qlora' or leave blank to train all parameters in original model
adapter: lora adapter: lora
# if you already have a lora model trained that you want to load, put that here # if you already have a lora model trained that you want to load, put that here
# lora hyperparameters # lora hyperparameters
@@ -293,6 +295,9 @@ torchdistx_path:
# Debug mode # Debug mode
debug: debug:
# Seed
seed:
``` ```
</details> </details>