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README.md

@@ -0,0 +1,77 @@
+---
+library_name: transformers
+license: other
+base_model: qnguyen3/vylinh-qwen-3b-merged
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: vylinh-dpo-v4
+  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. -->
+
+# vylinh-dpo-v4
+
+This model is a fine-tuned version of [qnguyen3/vylinh-qwen-3b-merged](https://huggingface.co/qnguyen3/vylinh-qwen-3b-merged) on the dpo_mix_vi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4053
+- Rewards/chosen: 2.9905
+- Rewards/rejected: -1.6223
+- Rewards/accuracies: 0.7143
+- Rewards/margins: 4.6128
+- Logps/rejected: -596.4308
+- Logps/chosen: -706.0082
+- Logits/rejected: -2.3770
+- Logits/chosen: -2.8608
+
+## 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-07
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- total_eval_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
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.3646        | 0.9995 | 1368 | 0.3423          | 3.0067         | 0.1768           | 0.7143             | 2.8299          | -578.4399      | -705.8457    | -2.3914         | -2.8822       |
+| 0.1542        | 1.9996 | 2737 | 0.3495          | 2.9122         | -0.7397          | 0.75               | 3.6519          | -587.6050      | -706.7914    | -2.3921         | -2.8787       |
+| 0.0501        | 2.9998 | 4106 | 0.3891          | 3.0809         | -1.3165          | 0.7143             | 4.3974          | -593.3735      | -705.1045    | -2.3870         | -2.8676       |
+| 0.0124        | 3.9978 | 5472 | 0.4053          | 2.9905         | -1.6223          | 0.7143             | 4.6128          | -596.4308      | -706.0082    | -2.3770         | -2.8608       |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.5.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.1

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all_results.json

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+    "eval_loss": 0.40534183382987976,
+    "eval_rewards/accuracies": 0.7142857313156128,
+    "eval_rewards/chosen": 2.9905052185058594,
+    "eval_rewards/margins": 4.6127777099609375,
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+    "total_flos": 519662108934144.0,
+    "train_loss": 0.17924007512469045,
+    "train_runtime": 53882.8337,
+    "train_samples_per_second": 3.251,
+    "train_steps_per_second": 0.102
+}

config.json

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+  "vocab_size": 151936
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eval_results.json

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+    "eval_steps_per_second": 0.979
+}

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special_tokens_map.json

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train_results.json

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