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: 0.4717
-- Accuracy: 0.8676
-- F1: 0.9046
+- Loss: 0.6354
+- Accuracy: 0.8701
+- F1: 0.9062
 
 ## Model description
 
@@ -38,27 +37,16 @@ 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:
-- learning_rate: 1.6000000000000003e-05
+- learning_rate: 1.2800000000000003e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 30
+- num_epochs: 40
 
 ### Training results
 
@@ -84,21 +72,30 @@ The following hyperparameters were used during training:
 | 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          |
+| 0.2211        | 21.0  | 4830 | 0.8456   | 0.8901 | 0.4070          |
+| 0.2136        | 22.0  | 5060 | 0.8578   | 0.8972 | 0.4090          |
+| 0.2136        | 23.0  | 5290 | 0.8578   | 0.8961 | 0.4328          |
+| 0.1774        | 24.0  | 5520 | 0.8382   | 0.8791 | 0.4602          |
+| 0.1774        | 25.0  | 5750 | 0.8627   | 0.9018 | 0.4551          |
+| 0.1774        | 26.0  | 5980 | 0.8505   | 0.8920 | 0.4677          |
+| 0.1521        | 27.0  | 6210 | 0.8578   | 0.8953 | 0.4854          |
+| 0.1521        | 28.0  | 6440 | 0.8505   | 0.8932 | 0.5064          |
+| 0.134         | 29.0  | 6670 | 0.8603   | 0.8988 | 0.4971          |
+| 0.134         | 30.0  | 6900 | 0.8676   | 0.9046 | 0.4717          |
+| 0.1298        | 31.0  | 7130 | 0.5216   | 0.8652 | 0.8998          |
+| 0.1298        | 32.0  | 7360 | 0.5339   | 0.8578 | 0.8979          |
+| 0.1233        | 33.0  | 7590 | 0.5533   | 0.8627 | 0.8993          |
+| 0.1233        | 34.0  | 7820 | 0.5526   | 0.875  | 0.9084          |
+| 0.1094        | 35.0  | 8050 | 0.6027   | 0.8725 | 0.9068          |
+| 0.1094        | 36.0  | 8280 | 0.6441   | 0.8652 | 0.9037          |
+| 0.0906        | 37.0  | 8510 | 0.6289   | 0.8554 | 0.8929          |
+| 0.0906        | 38.0  | 8740 | 0.6213   | 0.8676 | 0.9039          |
+| 0.0906        | 39.0  | 8970 | 0.6585   | 0.8603 | 0.8977          |
+| 0.0842        | 40.0  | 9200 | 0.6354   | 0.8701 | 0.9062          |
 
 
 ### Framework versions
 
-- PEFT 0.4.0
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5