update model card README.md

README.md

@@ -10,7 +10,6 @@ metrics:
 model-index:
 - name: Llama-2-7b-hf-finetuned-mrpc-v0.4
   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: 0.4165
-- Accuracy: 0.8505
-- F1: 0.8928
+- Loss: 0.4717
+- Accuracy: 0.8676
+- F1: 0.9046
 
 ## 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:
@@ -58,7 +46,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 20
+- num_epochs: 30
 
 ### Training results
 
@@ -80,15 +68,24 @@ The following hyperparameters were used during training:
 | 0.2799        | 14.0  | 3220 | 0.8456   | 0.8881 | 0.3873          |
 | 0.2799        | 15.0  | 3450 | 0.8529   | 0.8940 | 0.3939          |
 | 0.2511        | 16.0  | 3680 | 0.8431   | 0.8877 | 0.4018          |
-| 0.2511        | 17.0  | 3910 | 0.3969   | 0.8529 | 0.8947          |
-| 0.2371        | 18.0  | 4140 | 0.3963   | 0.8456 | 0.8912          |
-| 0.2371        | 19.0  | 4370 | 0.3865   | 0.8578 | 0.8964          |
-| 0.2211        | 20.0  | 4600 | 0.4165   | 0.8505 | 0.8928          |
+| 0.2511        | 17.0  | 3910 | 0.8529   | 0.8947 | 0.3969          |
+| 0.2371        | 18.0  | 4140 | 0.8456   | 0.8912 | 0.3963          |
+| 0.2371        | 19.0  | 4370 | 0.8578   | 0.8964 | 0.3865          |
+| 0.2211        | 20.0  | 4600 | 0.8505   | 0.8928 | 0.4165          |
+| 0.2211        | 21.0  | 4830 | 0.4070   | 0.8456 | 0.8901          |
+| 0.2136        | 22.0  | 5060 | 0.4090   | 0.8578 | 0.8972          |
+| 0.2136        | 23.0  | 5290 | 0.4328   | 0.8578 | 0.8961          |
+| 0.1774        | 24.0  | 5520 | 0.4602   | 0.8382 | 0.8791          |
+| 0.1774        | 25.0  | 5750 | 0.4551   | 0.8627 | 0.9018          |
+| 0.1774        | 26.0  | 5980 | 0.4677   | 0.8505 | 0.8920          |
+| 0.1521        | 27.0  | 6210 | 0.4854   | 0.8578 | 0.8953          |
+| 0.1521        | 28.0  | 6440 | 0.5064   | 0.8505 | 0.8932          |
+| 0.134         | 29.0  | 6670 | 0.4971   | 0.8603 | 0.8988          |
+| 0.134         | 30.0  | 6900 | 0.4717   | 0.8676 | 0.9046          |
 
 
 ### Framework versions
 
-- PEFT 0.4.0
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5