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Model: W-61/llama-3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260417-230753
Source: Original Platform

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README.md

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+---
+library_name: transformers
+base_model: llama-3-8b-base-sft-hh-helpful-4xh200-batch-64
+tags:
+- alignment-handbook
+- beta-dpo
+- generated_from_trainer
+datasets:
+- Anthropic/hh-rlhf
+model-index:
+- name: llama-3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260417-230753
+  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-3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260417-230753
+
+This model is a fine-tuned version of [llama-3-8b-base-sft-hh-helpful-4xh200-batch-64](https://huggingface.co/llama-3-8b-base-sft-hh-helpful-4xh200-batch-64) on the Anthropic/hh-rlhf dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7101
+- Beta Dpo/beta: 0.0691
+- Beta Dpo/loss Margin Mean: 86.8606
+- Beta Dpo/beta Margin Mean: 10.0274
+- Beta Dpo/beta Margin Std: 12.8117
+- Beta Dpo/beta Margin Grad Mean: -0.4550
+- Beta Dpo/beta Margin Grad Std: 0.0744
+- Beta Dpo/gap Mean: 130.0152
+- Beta Dpo/gap Std: 165.0541
+- Beta Dpo/beta Used Raw: -2.4893
+- Beta Dpo/beta Used: 0.0691
+- Beta Dpo/mask Keep Frac: 1.0
+- Logits/chosen: -0.2789
+- Logits/rejected: -0.2575
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- total_eval_batch_size: 32
+- optimizer: Use OptimizerNames.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: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Beta Dpo/beta | Beta Dpo/loss Margin Mean | Beta Dpo/beta Margin Mean | Beta Dpo/beta Margin Std | Beta Dpo/beta Margin Grad Mean | Beta Dpo/beta Margin Grad Std | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected |
+|:-------------:|:------:|:----:|:---------------:|:-------------:|:-------------------------:|:-------------------------:|:------------------------:|:------------------------------:|:-----------------------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
+| 0.9552        | 0.1468 | 100  | 0.6786          | 0.0046        | 9.8098                    | 0.0725                    | 0.1096                   | -0.4895                        | 0.0167                        | 17.6954           | 22.1843          | -0.3731                | 0.0046             | 1.0                     | -0.6698       | -0.6418         |
+| 0.8706        | 0.2937 | 200  | 0.6904          | 0.0046        | 27.7458                   | 0.2199                    | 0.3260                   | -0.4903                        | 0.0228                        | 50.6913           | 68.2433          | -1.2767                | 0.0046             | 1.0                     | -0.6064       | -0.5873         |
+| 2.8698        | 0.4405 | 300  | 0.8542          | 0.0215        | 46.8593                   | 1.7761                    | 2.5216                   | -0.4710                        | 0.0500                        | 79.1242           | 110.1004         | -1.8359                | 0.0215             | 1.0                     | -0.4178       | -0.4010         |
+| 18.5063       | 0.5874 | 400  | 0.7607          | 0.0093        | 66.8920                   | 1.0762                    | 1.4305                   | -0.4753                        | 0.0447                        | 116.2162          | 143.8824         | -2.8595                | 0.0093             | 1.0                     | -0.4157       | -0.3938         |
+| 1.1587        | 0.7342 | 500  | 1.3024          | 0.0541        | 78.1021                   | 7.2488                    | 9.0766                   | -0.4557                        | 0.0679                        | 118.3478          | 142.3098         | -2.3147                | 0.0541             | 1.0                     | -0.3590       | -0.3353         |
+| 4.9835        | 0.8811 | 600  | 1.7101          | 0.0691        | 86.8606                   | 10.0274                   | 12.8117                  | -0.4550                        | 0.0744                        | 130.0152          | 165.0541         | -2.4893                | 0.0691             | 1.0                     | -0.2789       | -0.2575         |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.21.4

all_results.json

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+    "eval_beta_dpo/beta": 0.011150650680065155,
+    "eval_beta_dpo/beta_margin_grad_mean": -0.47102445363998413,
+    "eval_beta_dpo/beta_margin_grad_std": 0.049201950430870056,
+    "eval_beta_dpo/beta_margin_mean": 1.640921711921692,
+    "eval_beta_dpo/beta_margin_std": 2.0729942321777344,
+    "eval_beta_dpo/beta_used": 0.011150650680065155,
+    "eval_beta_dpo/beta_used_raw": -3.504255771636963,
+    "eval_beta_dpo/gap_mean": 147.1534881591797,
+    "eval_beta_dpo/gap_std": 168.50018310546875,
+    "eval_beta_dpo/loss_margin_mean": 87.08258056640625,
+    "eval_beta_dpo/mask_keep_frac": 1.0,
+    "eval_logits/chosen": -0.2772989273071289,
+    "eval_logits/rejected": -0.2549748718738556,
+    "eval_loss": 0.7894024848937988,
+    "eval_runtime": 40.1139,
+    "eval_samples": 2339,
+    "eval_samples_per_second": 58.309,
+    "eval_steps_per_second": 1.845,
+    "total_flos": 0.0,
+    "train_loss": 2.627565469291942,
+    "train_runtime": 3177.7378,
+    "train_samples": 43598,
+    "train_samples_per_second": 13.72,
+    "train_steps_per_second": 0.214
+}

config.json

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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
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+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.0",
+  "use_cache": true,
+  "vocab_size": 128256
+}

eval_results.json

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+    "eval_beta_dpo/beta_margin_grad_mean": -0.47102445363998413,
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+    "eval_steps_per_second": 1.845
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+  "max_length": 4096,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.51.0"
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