SylvanL
/

ChatTCM-7B-SFT

@@ -11,197 +11,56 @@ base_model:
 - SylvanL/ChatTCM-7B-Pretrain
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 - SylvanL/ChatTCM-7B-Pretrain
 ---
+在2张V800-80G上,
+基于SylvanL/ChatTCM-7B-Pretrain,
+使用SylvanL/Traditional-Chinese-Medicine-Dataset-SFT进行了1个epoch的有监督微调(Supervised Fine-tuning).
+```
+epoch 1:
+    "epoch": 0.9999178959467966,
+    "num_input_tokens_seen": 1649269888,
+    "total_flos": 3298213988794368.0,
+    "train_loss": 1.0691444667014194,
+    "train_runtime": 587389.2072,
+    "train_samples_per_second": 3.483,
+    "train_steps_per_second": 0.016
+```
+```
+llamafactory-cli train \
+    --stage sft \
+    --do_train True \
+    --model_name_or_path {model_name_or_path} \
+    --preprocessing_num_workers 16 \
+    --finetuning_type full \
+    --template default \
+    --flash_attn auto \
+    --dataset_dir {dataset_dir} \
+    --dataset SFT_medicalKnowledge_source1_548404,SFT_medicalKnowledge_source2_99334,SFT_medicalKnowledge_source3_556540,SFT_nlpDiseaseDiagnosed_61486,SFT_nlpSyndromeDiagnosed_48665,SFT_structGeneral_310860,SFT_structPrescription_92896,SFT_external_traditionalTrans_7304,SFT_external_shuffledCOIGCQIA_44694,_SFT_external_shuffledCOIG_275985 \
+    --cutoff_len 1024 \
+    --learning_rate 5e-05 \
+    --num_train_epochs 1.0 \
+    --max_samples 1000000 \
+    --per_device_train_batch_size 28 \
+    --gradient_accumulation_steps 4 \
+    --lr_scheduler_type cosine \
+    --max_grad_norm 1.0 \
+    --logging_steps 1 \
+    --save_steps 1000 \
+    --warmup_steps 0 \
+    --optim adamw_torch \
+    --packing False \
+    --report_to none \
+    --output_dir {output_dir} \
+    --bf16 True \
+    --plot_loss True \
+    --ddp_timeout 180000000 \
+    --include_num_input_tokens_seen True \
+    --deepspeed cache/ds_z3_offload_config.json
+```