Model save

README.md

@@ -1,23 +1,85 @@
 ---
-language:
-- en
 license: apache-2.0
+library_name: peft
 tags:
-- text-generation-inference
-- transformers
-- unsloth
-- llama
 - trl
 - orpo
+- unsloth
+- generated_from_trainer
 base_model: cognitivecomputations/dolphin-2.9.1-yi-1.5-9b
+model-index:
+- name: Gaston_dolphin-2.9.1-yi-1.5-9b
+  results: []
 ---
 
-# Uploaded  model
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bacoco/Gaston_dolphin-2.9.1-yi-1.5-9b/runs/4d2n86g4)
+# Gaston_dolphin-2.9.1-yi-1.5-9b
+
+This model is a fine-tuned version of [cognitivecomputations/dolphin-2.9.1-yi-1.5-9b](https://huggingface.co/cognitivecomputations/dolphin-2.9.1-yi-1.5-9b) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4290
+- Rewards/chosen: -0.0153
+- Rewards/rejected: -0.2895
+- Rewards/accuracies: 0.9985
+- Rewards/margins: 0.2742
+- Logps/rejected: -2.8952
+- Logps/chosen: -0.1528
+- Logits/rejected: -0.1534
+- Logits/chosen: 0.0002
+- Nll Loss: 0.4278
+- Log Odds Ratio: -0.0124
+- Log Odds Chosen: 4.8981
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 8e-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
+| 0.5193        | 0.1005 | 103  | 0.5159          | -0.0187        | -0.0825          | 0.9971             | 0.0638          | -0.8248        | -0.1866      | 0.1547          | 0.1467        | 0.5004   | -0.1555        | 2.0327          |
+| 0.4988        | 0.2009 | 206  | 0.4724          | -0.0170        | -0.1413          | 0.9985             | 0.1243          | -1.4130        | -0.1703      | 0.0154          | -0.0134       | 0.4661   | -0.0627        | 3.0432          |
+| 0.4375        | 0.3014 | 309  | 0.4577          | -0.0162        | -0.1628          | 0.9985             | 0.1466          | -1.6283        | -0.1622      | 0.1372          | 0.1328        | 0.4530   | -0.0467        | 3.3955          |
+| 0.4738        | 0.4019 | 412  | 0.4463          | -0.0160        | -0.2198          | 0.9985             | 0.2038          | -2.1980        | -0.1596      | -0.0220         | 0.0649        | 0.4438   | -0.0250        | 4.0928          |
+| 0.4893        | 0.5023 | 515  | 0.4406          | -0.0159        | -0.2499          | 0.9985             | 0.2341          | -2.4993        | -0.1585      | -0.0720         | 0.0474        | 0.4388   | -0.0185        | 4.4389          |
+| 0.4565        | 0.6028 | 618  | 0.4357          | -0.0157        | -0.3289          | 0.9985             | 0.3133          | -3.2895        | -0.1566      | -0.1392         | 0.0470        | 0.4347   | -0.0093        | 5.2916          |
+| 0.4069        | 0.7032 | 721  | 0.4324          | -0.0154        | -0.3096          | 0.9985             | 0.2942          | -3.0962        | -0.1544      | -0.1833         | -0.0044       | 0.4313   | -0.0107        | 5.1028          |
+| 0.4297        | 0.8037 | 824  | 0.4299          | -0.0153        | -0.2854          | 0.9985             | 0.2701          | -2.8536        | -0.1528      | -0.1911         | -0.0397       | 0.4286   | -0.0129        | 4.8536          |
+| 0.4437        | 0.9042 | 927  | 0.4290          | -0.0153        | -0.2895          | 0.9985             | 0.2742          | -2.8952        | -0.1528      | -0.1534         | 0.0002        | 0.4278   | -0.0124        | 4.8981          |
 
-- **Developed by:** baconnier
-- **License:** apache-2.0
-- **Finetuned from model :** cognitivecomputations/dolphin-2.9.1-yi-1.5-9b
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+### Framework versions
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+- PEFT 0.11.1
+- Transformers 4.41.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

adapter_model.safetensors

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