update model card README.md

README.md

@@ -10,7 +10,6 @@ metrics:
 model-index:
 - name: Llama-2-7b-hf-finetuned-mrpc-v5
   results: []
-library_name: peft
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 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 glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6758
 - Accuracy: 0.8578
 - F1: 0.8986
+- Loss: 0.6758
 
 ## Model description
 
@@ -38,17 +37,6 @@ More information needed
 
 ## Training procedure
 
-
-The following `bitsandbytes` quantization config was used during training:
-- load_in_8bit: True
-- load_in_4bit: False
-- 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: fp4
-- bnb_4bit_use_double_quant: False
-- bnb_4bit_compute_dtype: float32
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -76,14 +64,13 @@ The following hyperparameters were used during training:
 | 0.42          | 10.0  | 9170  | 0.8407   | 0.8862 | 0.5576          |
 | 0.3678        | 11.0  | 10087 | 0.8480   | 0.8927 | 0.6212          |
 | 0.3453        | 12.0  | 11004 | 0.8480   | 0.8916 | 0.6070          |
-| 0.353         | 13.0  | 11921 | 0.6705   | 0.8529 | 0.8958          |
-| 0.3257        | 14.0  | 12838 | 0.6579   | 0.8407 | 0.8845          |
-| 0.3047        | 15.0  | 13755 | 0.6758   | 0.8578 | 0.8986          |
+| 0.353         | 13.0  | 11921 | 0.8529   | 0.8958 | 0.6705          |
+| 0.3257        | 14.0  | 12838 | 0.8407   | 0.8845 | 0.6579          |
+| 0.3047        | 15.0  | 13755 | 0.8578   | 0.8986 | 0.6758          |
 
 
 ### Framework versions
 
-- PEFT 0.4.0
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5