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Model: jackf857/llama-3-8b-base-slic-hf-ultrafeedback-4xh200
Source: Original Platform

README.md

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+---
+library_name: transformers
+base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
+tags:
+- alignment-handbook
+- slic-hf
+- generated_from_trainer
+datasets:
+- HuggingFaceH4/ultrafeedback_binarized
+model-index:
+- name: llama-3-8b-base-slic-hf-ultrafeedback-8xh200
+  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-slic-hf-ultrafeedback-8xh200
+
+This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
+It achieves the following results on the evaluation set:
+- Loss: 341.9101
+- Rewards/chosen: -260.8732
+- Rewards/rejected: -246.9854
+- Rewards/accuracies: 0.4919
+- Rewards/margins: -13.8878
+- Logps/chosen: -260.8732
+- Logps/rejected: -246.9854
+- Slic/rank Loss: 81.0369
+- Slic/ce Loss: 260.8732
+- Logits/chosen: -0.5998
+- Logits/rejected: -0.6056
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Slic/rank Loss | Slic/ce Loss | Logits/chosen | Logits/rejected |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:--------------:|:------------:|:-------------:|:---------------:|
+| 1368.2239     | 0.4188 | 200  | 345.5856        | -262.1702      | -246.1536        | 0.4874             | -16.0166        | -262.1702    | -246.1536      | 83.4155        | 262.1702     | -0.6125       | -0.6205         |
+| 1395.7896     | 0.8377 | 400  | 341.9101        | -260.8732      | -246.9854        | 0.4919             | -13.8878        | -260.8732    | -246.9854      | 81.0369        | 260.8732     | -0.5998       | -0.6056         |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.21.4