End of training
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- adapter_model.bin +1 -1
README.md
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---
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library_name: peft
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license: other
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base_model: SeaLLMs/
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tags:
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- axolotl
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- generated_from_trainer
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model-index:
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- name: proof-reading-
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results: []
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---
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@@ -18,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
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axolotl version: `0.5.0`
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```yaml
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base_model: SeaLLMs/
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trust_remote_code: true
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load_in_8bit: false
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strict: false
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datasets:
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- path: Tippawan/
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type: chat_template
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conversation: chatml
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field_messages: messages
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pad_to_sequence_len: false
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push_to_hub: true
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hub_model_id: Tippawan/proof-reading-
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use_auth_token: true # Ensure you have set your Hugging Face API token in the environment
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hub_private_repo: true # Set to true if you want the repository to be private
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hub_strategy: all_checkpoints
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load_best_model_at_end: true
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adapter: lora
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lora_model_dir:
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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wandb_project: proof-reading-
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wandb_entity:
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wandb_watch:
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wandb_name:
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs:
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optimizer: adamw_torch
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lr_scheduler: cosine
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learning_rate: 0.0002
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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# proof-reading-
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This model is a fine-tuned version of [SeaLLMs/
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## Model description
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- num_epochs:
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### Training results
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---
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library_name: peft
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license: other
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base_model: SeaLLMs/SeaLLMs-v3-7B-Chat
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tags:
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- axolotl
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- generated_from_trainer
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model-index:
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- name: proof-reading-hl-v1
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results: []
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---
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axolotl version: `0.5.0`
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```yaml
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base_model: SeaLLMs/SeaLLMs-v3-7B-Chat
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trust_remote_code: true
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load_in_8bit: false
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strict: false
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datasets:
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- path: Tippawan/hl-2
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type: chat_template
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conversation: chatml
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field_messages: messages
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pad_to_sequence_len: false
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push_to_hub: true
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hub_model_id: Tippawan/proof-reading-hl-v1 # Replace with your Hugging Face repo ID
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use_auth_token: true # Ensure you have set your Hugging Face API token in the environment
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hub_private_repo: true # Set to true if you want the repository to be private
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hub_strategy: all_checkpoints
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load_best_model_at_end: true
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adapter: lora
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lora_model_dir:
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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wandb_project: proof-reading-hl-v1
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wandb_entity:
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wandb_watch:
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wandb_name:
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 10 #editted 3
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optimizer: adamw_torch
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lr_scheduler: cosine
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learning_rate: 0.0002
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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# proof-reading-hl-v1
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This model is a fine-tuned version of [SeaLLMs/SeaLLMs-v3-7B-Chat](https://huggingface.co/SeaLLMs/SeaLLMs-v3-7B-Chat) on the None dataset.
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## Model description
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- num_epochs: 10
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### Training results
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 161621802
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:005442da11bab27e4487afab889afb5a1983f44da1667266a9bd4c6f9cb933d1
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size 161621802
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