10 epoch

README.md

@@ -37,8 +37,8 @@ Since [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-j
 
 Using the [gemma-2-2b base model](https://huggingface.co/google/gemma-2-2b), I employed the ORPO method described by [mlabonne](https://towardsdatascience.com/fine-tune-llama-3-with-orpo-56cfab2f9ada) but the input model was read into VRAM by [unsloth](https://github.com/unslothai/unsloth) to allow using the full 40k dataset to run on a single 3090.
 
-Five epoches was run. Smallest eval_loss was achieve at epoch 4.96. 
-Checkpoint at epoch 4.96 is used to obtain a model adapter and
+Five epoches was run. Smallest eval_loss was achieve at epoch 7.72. 
+Checkpoint at epoch 7.72 is used to obtain a model adapter and
 applied it to [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-jpn-it-abliterated-18) to obtain [gemma-2-2b-ORPO-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18).
 
 | Epoch | loss | eval_loss | eval_logps/rejected | eval_logps/chosen |
@@ -49,6 +49,12 @@ applied it to [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemm
 | 4.00 | 1.5293 | 1.0166 | -1.2004 | -0.7200 |
 | 4.96 | 1.2893 | 1.0077 | -1.1754 | -0.7106 |
 | 5.00 | 1.3458 | 1.0078 | -1.1730 | -0.7105 |
+| 6.00 | 1.3807 | 0.9924 | -1.1757 | -0.6971 |
+| 7.00 | 1.0855 | 0.9889 | -1.2634 | -0.7235 |
+| 7.72 | 0.8720 | 0.9855 | -1.2374 | -0.7100 |
+| 8.00 | 0.7301 | 0.9864 | -1.2406 | -0.7113 |
+| 9.00 | 1.1939 | 0.9934 | -1.2703 | -0.6852 |
+| 10.00 | 0.7421 | 1.0269 | -1.2552 | -0.7395 |
 
 Then I followed Rombodawg's [suggestion](https://www.reddit.com/r/LocalLLaMA/comments/1fyx27y/im_pretty_happy_with_how_my_method_worked_out/) to merge [gemma-2-2b](https://huggingface.co/google/gemma-2-2b), [gemma-2-2b-ORPO-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18) and [gemma-2-2b-jpn-it-ablitered-18](https://huggingface.co/ymcki/gemma-2-2b-jpn-it-abliterated-18) to obtain this model.
 
@@ -61,52 +67,14 @@ Click on the model name go to the raw score json generated by Open LLM Leaderboa
 | Model | Average | IFEval | BHH | Math Lv5 | GPQA | MUSR | MMLU-PRO |
 | ----- | ------- | ------ | ----|--------- | ---- | ---- | -------- |
 | [gemma-2-2b-jpn-it](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/google/gemma-2-2b-jpn-it/results_2024-10-15T15-21-39.173019.json) | 30.82 | 54.11 | 41.43 | 0.0 | 27.52 | 37.17 | 24.67 |
-| gemma-2-2b-ORPO-jpn-it-abliterated-18 (5 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
-| gemma-2-2b-ORPO-jpn-it-abliterated-18-merge (5 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
+| [gemma-2-2b-ORPO-jpn-it-abliterated-18-merge (5 epoches)](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18-merge/results_2024-10-30T17-06-58.119904.json) | 29.26 | 49.16 | 38.15 | 2.49 | 28.19 | 33.07 | 24.51 |
+| gemma-2-2b-ORPO-jpn-it-abliterated-18-merge (10 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
+| [gemma-2-2b-ORPO-jpn-it-abliterated-18 (5 epoches)](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18/results_2024-10-30T22-19-29.202883.json) | 29.57 | 48.05 | 41.26 | 0.0 | 27.18 | 36.51 | 24.43
+| gemma-2-2b-ORPO-jpn-it-abliterated-18 (10 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
 | [gemma-2-2b-jpn-it-abliterated-17](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-17/results_2024-10-18T15-18-46.821674.json) | 30.29 | 52.65 | 40.46 | 0.0 | 27.18 | 36.90 | 24.55 |
 | [gemma-2-2b-jpn-it-abliterated-18](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-18/results_2024-10-18T15-41-42.399571.json) | 30.61 | 53.02 | 40.96 | 0.0 | 27.35 | 37.30 | 25.05 |
 | [gemma-2-2b-jpn-it-abliterated-24](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-24/results_2024-10-25T16-29-46.542899.json) | 30.61 | 51.37 | 40.77 | 0.0 | 27.77 | 39.02 | 24.73 |
 
-## Merge Details
-### Merge Method
-
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
-
-This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) as a base.
-
-### Models Merged
-
-The following models were included in the merge:
-* ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
-* ymcki/gemma-2-2b-jpn-it-abliterated-18
-
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-models:
-  - model: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
-    dtype: bfloat16
-    parameters:
-      density: 1.0
-      weight: 1.0
-  - model: ymcki/gemma-2-2b-jpn-it-abliterated-18
-    dtype: bfloat16
-    parameters:
-      density: 1.0
-      weight: 1.0
-merge_method: ties
-base_model: google/gemma-2-2b
-parameters:
-  density: 1.0
-  weight: 1.0
-  normalize: true
-  int8_mask: true
-dtype: bfloat16
-tokenizer_source: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
-```
-
 ## How to run this model
 
 ```py

mergekit_config.yml

@@ -1,10 +1,10 @@
 models:
-  - model: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
+  - model: ./gemma-2-2b-ORPO-jpn-it-abliterated-18
     dtype: bfloat16
     parameters:
       density: 1.0
       weight: 1.0
-  - model: ymcki/gemma-2-2b-jpn-it-abliterated-18
+  - model: /home/user/gemma-2-2b-jpn-it-abliterated-18
     dtype: bfloat16
     parameters:
       density: 1.0
@@ -17,4 +17,4 @@ parameters:
   normalize: true
   int8_mask: true
 dtype: bfloat16
-tokenizer_source: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
+tokenizer_source: ./gemma-2-2b-ORPO-jpn-it-abliterated-18

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