Model save

README.md

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+---
+library_name: peft
+license: llama3.1
+base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
+tags:
+- trl
+- kto
+- llama-factory
+- generated_from_trainer
+model-index:
+- name: Llama-3.1-8B-Instruct-KTO-300
+  results: []
+---
+
+<!-- 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. -->
+
+# Llama-3.1-8B-Instruct-KTO-300
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2807
+- Rewards/chosen: 0.7524
+- Logps/chosen: -12.9007
+- Logits/chosen: -3652706.0
+- Rewards/rejected: -1.5384
+- Logps/rejected: -37.9030
+- Logits/rejected: -7997593.7778
+- Rewards/margins: 2.2908
+- Kl: 0.6633
+
+## 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: 5e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Logps/chosen | Logits/chosen | Rewards/rejected | Logps/rejected | Logits/rejected | Rewards/margins |         |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:-------------:|:----------------:|:--------------:|:---------------:|:---------------:|:-------:|
+| 0.4973        | 1.4889 | 50   | 0.4995          | 0.0407         | -20.0184     | -5131056.3333 | 0.0319           | -22.1998       | -8269521.7778   | 0.0088          | 4.2481  |
+| 0.4683        | 2.9778 | 100  | 0.4692          | 0.3686         | -16.7392     | -4839914.0    | 0.0514           | -22.0054       | -8194471.1111   | 0.3172          | 12.3862 |
+| 0.3709        | 4.4741 | 150  | 0.3692          | 0.5681         | -14.7444     | -4248186.6667 | -0.5877          | -28.3963       | -8021952.0      | 1.1558          | 2.0650  |
+| 0.3219        | 5.9630 | 200  | 0.3044          | 0.6412         | -14.0130     | -3768132.0    | -1.2363          | -34.8816       | -7958945.7778   | 1.8775          | 1.4612  |
+| 0.2882        | 7.4593 | 250  | 0.2864          | 0.7339         | -13.0862     | -3685730.3333 | -1.4520          | -37.0385       | -7991116.4444   | 2.1858          | 0.8725  |
+| 0.2574        | 8.9481 | 300  | 0.2807          | 0.7524         | -12.9007     | -3652706.0    | -1.5384          | -37.9030       | -7997593.7778   | 2.2908          | 0.6633  |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.46.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3

adapter_model.safetensors

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