Model save

README.md

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+---
+license: llama3
+base_model: meta-llama/Meta-Llama-3-8B
+tags:
+- generated_from_trainer
+model-index:
+- name: zephyr-7b-dpo-full
+  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. -->
+
+# zephyr-7b-dpo-full
+
+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 None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1891
+- Rewards/chosen: 0.2333
+- Rewards/rejected: -3.7392
+- Rewards/accuracies: 0.7579
+- Rewards/margins: 3.9725
+- Logps/rejected: -349.7088
+- Logps/chosen: -352.8180
+- Logits/rejected: -0.9260
+- Logits/chosen: -0.9366
+- Use Label: 3014.7302
+- Pred Label: 5005.2700
+
+## 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: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- 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/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Use Label | Pred Label |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:---------:|:----------:|
+| 0.1714        | 1.0   | 1910 | 0.1891          | 0.2333         | -3.7392          | 0.7579             | 3.9725          | -349.7088      | -352.8180    | -0.9260         | -0.9366       | 2959.7302 | 4808.2700  |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.1+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

all_results.json

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+{
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+    "eval_logits/chosen": -0.9365912079811096,
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+    "eval_logps/chosen": -352.8179626464844,
+    "eval_logps/rejected": -349.7088317871094,
+    "eval_loss": 0.18906600773334503,
+    "eval_pred_label": 5005.27001953125,
+    "eval_rewards/accuracies": 0.7579365372657776,
+    "eval_rewards/chosen": 0.2332553267478943,
+    "eval_rewards/margins": 3.972490072250366,
+    "eval_rewards/rejected": -3.7392351627349854,
+    "eval_runtime": 277.9429,
+    "eval_samples": 2000,
+    "eval_samples_per_second": 7.196,
+    "eval_steps_per_second": 0.227,
+    "eval_use_label": 3014.730224609375,
+    "train_loss": 0.2926436502271922,
+    "train_runtime": 13370.5554,
+    "train_samples": 61135,
+    "train_samples_per_second": 4.572,
+    "train_steps_per_second": 0.143
+}

eval_results.json

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+{
+    "epoch": 1.0,
+    "eval_logits/chosen": -0.9365912079811096,
+    "eval_logits/rejected": -0.926014244556427,
+    "eval_logps/chosen": -352.8179626464844,
+    "eval_logps/rejected": -349.7088317871094,
+    "eval_loss": 0.18906600773334503,
+    "eval_pred_label": 5005.27001953125,
+    "eval_rewards/accuracies": 0.7579365372657776,
+    "eval_rewards/chosen": 0.2332553267478943,
+    "eval_rewards/margins": 3.972490072250366,
+    "eval_rewards/rejected": -3.7392351627349854,
+    "eval_runtime": 277.9429,
+    "eval_samples": 2000,
+    "eval_samples_per_second": 7.196,
+    "eval_steps_per_second": 0.227,
+    "eval_use_label": 3014.730224609375
+}

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": "4.35.0"
+}

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train_results.json

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