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: 0.7271
-- Eval/rewards/chosen: 0.0966
-- Eval/logps/chosen: -206.6140
-- Eval/rewards/rejected: 0.0752
-- Eval/logps/rejected: -220.8250
-- Eval/rewards/margins: 0.0214
-- Eval/kl: 0.8580
+- 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
 
 ## Model description
 
@@ -43,25 +43,27 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 0.0001
 - train_batch_size: 1
 - eval_batch_size: 2
-- seed: 9012
+- seed: 1234
 - gradient_accumulation_steps: 8
 - total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 4.0
+- num_epochs: 6.0
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss |        |
-|:-------------:|:------:|:----:|:---------------:|:------:|
-| 0.5994        | 0.9412 | 12   | 0.7301          | 0.1561 |
-| 0.6           | 1.9608 | 25   | 0.7256          | 0.6149 |
-| 0.5831        | 2.9804 | 38   | 0.7234          | 0.8062 |
-| 0.6595        | 3.7647 | 48   | 0.7271          | 0.8580 |
+| 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 |
 
 
 ### Framework versions

adapter_config.json

@@ -20,10 +20,10 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "v_proj",
+    "o_proj",
     "k_proj",
     "q_proj",
-    "o_proj"
+    "v_proj"
   ],
   "task_type": "CAUSAL_LM",
   "use_dora": false,

adapter_model.safetensors

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metrics.jsonl

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+{"epoch": 2.96, "precision": 0.9999999933333334, "recall": 0.8333333287037037, "fold": 0}
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metrics_epoch_0.96_fold_0_lr_0.0001_seed_1234_weight_2.0.json

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metrics_epoch_2.0_fold_0_lr_0.0001_seed_1234_weight_2.0.json

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metrics_epoch_2.96_fold_0_lr_0.0001_seed_1234_weight_2.0.json

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metrics_epoch_4.0_fold_0_lr_0.0001_seed_1234_weight_2.0.json

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metrics_epoch_4.96_fold_0_lr_0.0001_seed_1234_weight_2.0.json

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metrics_epoch_5.76_fold_0_lr_0.0001_seed_1234_weight_2.0.json

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training_args.bin

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