Merge pull request AI4Finance-Foundation#181 from KPCOFGS/master

Update README.md

README.md

@@ -89,8 +89,8 @@ For detailed and more customized implementation, please refer to [FinGPT-Forecas
 
     **Cost per GPU hour.** For **A100 GPUs**, the AWS p4d.24xlarge instance, equipped with 8 A100 GPUs is used as a benchmark to estimate the costs. Note that BloombergGPT also used p4d.24xlarge As of July 11, 2023, the hourly rate for this instance stands at $32.773. Consequently, the estimated cost per GPU hour comes to $32.77 divided by 8, resulting in approximately **$4.10**. With this value as the reference unit price (1 GPU hour). **BloombergGPT estimated cost= 512 x 53 x 24 = 651,264 GPU hours x $4.10 = $2,670,182.40**. For **RTX 3090**, we assume its cost per hour is approximately **$1.0**, which is actually much higher than available GPUs from platforms like vast.ai.
 
-  * Reproduce the results by running [benchmarks](./fingpt/FinGPT_v3/benchmark/benchmarks.ipynb), and the detailed tutorial is on the way.
-  * Finetune your own FinGPT v3 model with the LoRA method on only an RTX 3090 with this [notebook](./fingpt/FinGPT_v3/training_8bit/train_Llama2_13B.ipynb) in 8bit or this [notebook](./fingpt/FinGPT_v3/training_int4/train.ipynb) in int4 (QLoRA)
+  * Reproduce the results by running [benchmarks](./fingpt/FinGPT_Sentiment_Analysis_v3/benchmark/benchmarks.ipynb), and the detailed tutorial is on the way.
+  * Finetune your own FinGPT v3 model with the LoRA method on only an RTX 3090 with this [notebook](./fingpt/FinGPT_Sentiment_Analysis_v3/training_8bit/train_Llama2_13B.ipynb) in 8bit or this [notebook](./fingpt/FinGPT_Sentiment_Analysis_v3/training_int4/train.ipynb) in int4 (QLoRA)
 
 * [FinGPT V1](./fingpt)
   + **FinGPT by finetuning ChatGLM2 / Llama2 with LoRA with the market-labeled data for the Chinese Market**