OsakanaTeishoku
/

Qwen2.5-7B-axolotl-sft-v0.2

@@ -1,166 +1,180 @@
----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-7B
-tags:
-- axolotl
-- generated_from_trainer
-datasets:
-- Aratako/Magpie-Tanuki-8B-annotated-96k
-- Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k
-- DataPilot/Zero_SFT_Ja_v2_b3t4
-model-index:
-- name: Qwen2.5-7B-axolotl-sft-v0.2
-  results: []
----
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
-axolotl version: `0.8.0`
-```yaml
-base_model: Qwen/Qwen2.5-7B
-hub_model_id: OsakanaTeishoku/Qwen2.5-7B-axolotl-sft-v0.2
-load_in_8bit: false
-load_in_4bit: true
-strict: false
-chat_template: qwen_25
-datasets:
-  # This will be the path used for the data when it is saved to the Volume in the cloud.
-  - path: Aratako/Magpie-Tanuki-8B-annotated-96k
-    split: train
-    type: chat_template
-    field_messages: messages
-  - path: Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k
-    split: train
-    type: chat_template
-    field_messages: messages
-  - path: DataPilot/Zero_SFT_Ja_v2_b3t4
-    split: train
-    type: chat_template
-    field_messages: conversation
-    message_property_mappings:
-      role: from
-      content: value
-shuffle_merged_datasets: true
-dataset_prepared_path: last_run_prepared
-#val_set_size: 0.05
-output_dir: ./lora-out
-sequence_len: 2048
-sample_packing: false
-eval_sample_packing: false
-pad_to_sequence_len: false
-adapter: qlora
-lora_model_dir:
-lora_r: 16
-lora_alpha: 32
-lora_dropout: 0.05
-lora_target_linear: true
-lora_fan_in_fan_out:
-lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral
-  - embed_tokens
-  - lm_head
-wandb_project: modal-axolotl
-wandb_name: 20250419-qwen7b-modal
-gradient_accumulation_steps: 4
-micro_batch_size: 16
-#auto_find_batch_size: true
-#num_epochs: 1
-optimizer: adamw_bnb_8bit
-lr_scheduler: cosine
-learning_rate: 0.0001
-bf16: true
-fp16: false
-tf32: false
-train_on_inputs: false
-group_by_length: false
-gradient_checkpointing: true
-early_stopping_patience:
-resume_from_checkpoint:
-local_rank:
-logging_steps: 1
-xformers_attention: true
-flash_attention:
-warmup_ratio: 0.05
-save_steps: 50
-max_steps: 200
-debug:
-#deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
-weight_decay: 0.0
-fsdp:
-fsdp_config:
-special_tokens:
-  eos_token: "<|im_end|>"
-plugins:
-  - axolotl.integrations.liger.LigerPlugin
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-liger_layer_norm: true
-liger_fused_linear_cross_entropy: true
-eval_strategy: "no"
-save_strategy: "steps"
-```
-</details><br>
-# Qwen2.5-7B-axolotl-sft-v0.2
-This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the Aratako/Magpie-Tanuki-8B-annotated-96k, the Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k and the DataPilot/Zero_SFT_Ja_v2_b3t4 datasets.
-## Model description
-More information needed
-## Intended uses & limitations
-More information needed
-## Training and evaluation data
-More information needed
-## Training procedure
-### Training hyperparameters
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 64
-- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 10
-- training_steps: 200
-### Training results
-### Framework versions
-- PEFT 0.15.1
-- Transformers 4.51.3
-- Pytorch 2.6.0+cu124
-- Datasets 3.5.0
 - Tokenizers 0.21.1

+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- Aratako/Magpie-Tanuki-8B-annotated-96k
+- Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k
+- DataPilot/Zero_SFT_Ja_v2_b3t4
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: Qwen2.5-7B-axolotl-sft-v0.2
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+axolotl version: `0.8.0`
+```yaml
+base_model: Qwen/Qwen2.5-7B
+hub_model_id: OsakanaTeishoku/Qwen2.5-7B-axolotl-sft-v0.2
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+chat_template: qwen_25
+datasets:
+  # This will be the path used for the data when it is saved to the Volume in the cloud.
+  - path: Aratako/Magpie-Tanuki-8B-annotated-96k
+    split: train
+    type: chat_template
+    field_messages: messages
+  - path: Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k
+    split: train
+    type: chat_template
+    field_messages: messages
+  - path: DataPilot/Zero_SFT_Ja_v2_b3t4
+    split: train
+    type: chat_template
+    field_messages: conversation
+    message_property_mappings:
+      role: from
+      content: value
+shuffle_merged_datasets: true
+dataset_prepared_path: last_run_prepared
+#val_set_size: 0.05
+output_dir: ./lora-out
+sequence_len: 2048
+sample_packing: false
+eval_sample_packing: false
+pad_to_sequence_len: false
+adapter: qlora
+lora_model_dir:
+lora_r: 16
+lora_alpha: 32
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral
+  - embed_tokens
+  - lm_head
+wandb_project: modal-axolotl
+wandb_name: 20250419-qwen7b-modal
+gradient_accumulation_steps: 4
+micro_batch_size: 16
+#auto_find_batch_size: true
+#num_epochs: 1
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0001
+bf16: true
+fp16: false
+tf32: false
+train_on_inputs: false
+group_by_length: false
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention: true
+flash_attention:
+warmup_ratio: 0.05
+save_steps: 50
+max_steps: 200
+debug:
+#deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  eos_token: "<|im_end|>"
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_glu_activation: true
+liger_layer_norm: true
+liger_fused_linear_cross_entropy: true
+eval_strategy: "no"
+save_strategy: "steps"
+```
+</details><br>
+# Qwen2.5-7B-axolotl-sft-v0.2
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the Aratako/Magpie-Tanuki-8B-annotated-96k, the Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k and the DataPilot/Zero_SFT_Ja_v2_b3t4 datasets.
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- training_steps: 200
+### Training results
+### Framework versions
+- PEFT 0.15.1
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
 - Tokenizers 0.21.1