update model card README.md

README.md

@@ -7,7 +7,6 @@ datasets:
 model-index:
 - name: llama2-finance
   results: []
-library_name: peft
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,8 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
 # llama2-finance
 
 This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the financial_phrasebank dataset.
-It achieves the following results on the evaluation set:
-- Loss: 2.2702
 
 ## Model description
 
@@ -33,17 +30,6 @@ More information needed
 
 ## Training procedure
 
-
-The following `bitsandbytes` quantization config was used during training:
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: False
-- bnb_4bit_compute_dtype: float16
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -55,7 +41,7 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- num_epochs: 1
+- training_steps: 20
 
 ### Training results
 
@@ -63,7 +49,6 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- PEFT 0.4.0
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu117
 - Datasets 2.14.4