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Model: W-61/llama-3-8b-base-sft-hh-harmless-4xh200
Source: Original Platform

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README.md

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+---
+library_name: transformers
+base_model: meta-llama/Meta-Llama-3-8B
+tags:
+- alignment-handbook
+- generated_from_trainer
+datasets:
+- Anthropic/hh-rlhf
+model-index:
+- name: llama-3-8b-base-sft-hh-harmless-4xh200-batch-64-20260416-181336
+  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-sft-hh-harmless-4xh200-batch-64-20260416-181336
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the Anthropic/hh-rlhf dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4830
+
+## 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: 2e-05
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.6483        | 0.4843 | 100  | 1.6259          |
+| 1.4519        | 0.9685 | 200  | 1.4830          |
+
+
+### 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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+{
+    "epoch": 0.9975786924939467,
+    "eval_loss": 1.4828004837036133,
+    "eval_runtime": 4.0547,
+    "eval_samples": 2303,
+    "eval_samples_per_second": 183.984,
+    "eval_steps_per_second": 5.919,
+    "total_flos": 7.598970652485222e+16,
+    "train_loss": 1.8085910475369795,
+    "train_runtime": 916.9479,
+    "train_samples": 42336,
+    "train_samples_per_second": 14.402,
+    "train_steps_per_second": 0.225
+}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "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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+{
+    "epoch": 0.9975786924939467,
+    "eval_loss": 1.4828004837036133,
+    "eval_runtime": 4.0547,
+    "eval_samples": 2303,
+    "eval_samples_per_second": 183.984,
+    "eval_steps_per_second": 5.919
+}

generation_config.json

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+{
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+  "do_sample": true,
+  "eos_token_id": 128001,
+  "max_length": 4096,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.51.0"
+}

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