End of training

README.md

@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5033
-- Eval/rewards/chosen: 2.8767
-- Eval/logps/chosen: -164.0585
-- Eval/rewards/rejected: 2.4882
-- Eval/logps/rejected: -204.9874
-- Eval/rewards/margins: 0.3885
-- Eval/kl: 24.2343
+- Loss: 0.5950
+- Eval/rewards/chosen: -0.0425
+- Eval/logps/chosen: -193.2501
+- Eval/rewards/rejected: -0.0817
+- Eval/logps/rejected: -230.6864
+- Eval/rewards/margins: 0.0392
+- Eval/kl: 0.0432
 
 ## Model description
 
@@ -43,7 +43,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 1e-05
 - train_batch_size: 1
 - eval_batch_size: 2
 - seed: 1234
@@ -56,14 +56,14 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss |         |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.6591        | 0.96  | 12   | 0.5834          | 0.2291  |
-| 0.3244        | 2.0   | 25   | 0.5716          | 15.3529 |
-| 0.0459        | 2.96  | 37   | 0.5362          | 20.4863 |
-| 0.07          | 4.0   | 50   | 0.5089          | 23.8717 |
-| 0.0208        | 4.96  | 62   | 0.4999          | 24.2550 |
-| 0.0416        | 5.76  | 72   | 0.5033          | 24.2343 |
+| Training Loss | Epoch | Step | Validation Loss |        |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.7975        | 0.96  | 12   | 0.5962          | 0.1577 |
+| 0.6733        | 2.0   | 25   | 0.5952          | 0.1152 |
+| 0.7717        | 2.96  | 37   | 0.5933          | 0.1001 |
+| 0.6599        | 4.0   | 50   | 0.5932          | 0.0620 |
+| 0.7354        | 4.96  | 62   | 0.5930          | 0.0628 |
+| 0.6221        | 5.76  | 72   | 0.5950          | 0.0432 |
 
 
 ### Framework versions

adapter_config.json

@@ -20,9 +20,9 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "o_proj",
-    "k_proj",
     "q_proj",
+    "k_proj",
+    "o_proj",
     "v_proj"
   ],
   "task_type": "CAUSAL_LM",

adapter_model.safetensors

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metrics.jsonl

@@ -28,3 +28,9 @@
 {"epoch": 4.0, "precision": 0.9999999923076924, "recall": 0.7222222182098765, "fold": 0}
 {"epoch": 4.96, "precision": 0.9999999928571429, "recall": 0.7777777734567901, "fold": 0}
 {"epoch": 5.76, "precision": 0.8888888839506173, "recall": 0.8888888839506173, "fold": 0}
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+{"epoch": 2.96, "precision": 0.51515151359045, "recall": 0.9444444391975308, "fold": 0}
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metrics_epoch_0.96_fold_0_lr_1e-05_seed_1234_weight_2.0.json

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metrics_epoch_2.0_fold_0_lr_1e-05_seed_1234_weight_2.0.json

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metrics_epoch_2.96_fold_0_lr_1e-05_seed_1234_weight_2.0.json

@@ -0,0 +1 @@
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metrics_epoch_4.0_fold_0_lr_1e-05_seed_1234_weight_2.0.json

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metrics_epoch_4.96_fold_0_lr_1e-05_seed_1234_weight_2.0.json

@@ -0,0 +1 @@
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metrics_epoch_5.76_fold_0_lr_1e-05_seed_1234_weight_2.0.json

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training_args.bin

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