Model save

README.md

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+---
+base_model: PKU-Alignment/alpaca-7b-reproduced
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: dpo-selective-alpaca
+  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. -->
+
+# dpo-selective-alpaca
+
+This model is a fine-tuned version of [PKU-Alignment/alpaca-7b-reproduced](https://huggingface.co/PKU-Alignment/alpaca-7b-reproduced) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4659.3857
+- Rewards/chosen: -0.2274
+- Rewards/rejected: -0.2645
+- Rewards/accuracies: 0.6342
+- Rewards/margins: 0.0372
+- Rewards/safe Rewards: -0.2254
+- Rewards/unsafe Rewards: -0.2253
+- Logps/rejected: -174.8009
+- Logps/chosen: -202.5513
+- Logits/rejected: -1.7296
+- Logits/chosen: -1.5835
+
+## 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: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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 | Rewards/safe Rewards | Rewards/unsafe Rewards | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------------:|:----------------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 4842.2766     | 0.11  | 500  | 4952.8877       | 0.0166         | 0.0096           | 0.6573             | 0.0070          | 0.0166               | 0.0165                 | -147.3908      | -178.1579    | -1.7834         | -1.6386       |
+| 4764.3852     | 0.22  | 1000 | 4865.9209       | -0.0099        | -0.0282          | 0.6644             | 0.0184          | -0.0094              | -0.0098                | -151.1701      | -180.8021    | -1.7281         | -1.5780       |
+| 4814.1586     | 0.32  | 1500 | 4783.4697       | -0.1011        | -0.1298          | 0.6566             | 0.0286          | -0.1003              | -0.1009                | -161.3237      | -189.9300    | -1.7085         | -1.5581       |
+| 4693.2395     | 0.43  | 2000 | 4735.1978       | -0.1597        | -0.1926          | 0.6480             | 0.0329          | -0.1583              | -0.1588                | -167.6019      | -195.7835    | -1.7080         | -1.5598       |
+| 4747.273      | 0.54  | 2500 | 4701.7651       | -0.1978        | -0.2321          | 0.6416             | 0.0344          | -0.1960              | -0.1962                | -171.5614      | -199.5948    | -1.7166         | -1.5693       |
+| 4464.0027     | 0.65  | 3000 | 4681.6167       | -0.2061        | -0.2411          | 0.6356             | 0.0350          | -0.2041              | -0.2043                | -172.4578      | -200.4294    | -1.7240         | -1.5768       |
+| 4613.8953     | 0.75  | 3500 | 4667.7300       | -0.2201        | -0.2561          | 0.6333             | 0.0360          | -0.2182              | -0.2182                | -173.9565      | -201.8304    | -1.7289         | -1.5822       |
+| 4642.2859     | 0.86  | 4000 | 4661.8745       | -0.2258        | -0.2627          | 0.6336             | 0.0369          | -0.2238              | -0.2238                | -174.6188      | -202.3950    | -1.7298         | -1.5833       |
+| 4747.2375     | 0.97  | 4500 | 4659.3687       | -0.2266        | -0.2638          | 0.6363             | 0.0372          | -0.2246              | -0.2245                | -174.7243      | -202.4745    | -1.7302         | -1.5838       |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2
+- Datasets 2.14.6
+- Tokenizers 0.15.0

all_results.json

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+    "eval_logps/rejected": -174.8009033203125,
+    "eval_loss": 4659.3857421875,
+    "eval_rewards/accuracies": 0.6341965198516846,
+    "eval_rewards/chosen": -0.22735264897346497,
+    "eval_rewards/margins": 0.03718877211213112,
+    "eval_rewards/rejected": -0.2645414173603058,
+    "eval_rewards/safe_rewards": -0.2253904640674591,
+    "eval_rewards/unsafe_rewards": -0.22526215016841888,
+    "eval_runtime": 1015.3903,
+    "eval_samples": 33044,
+    "eval_samples_per_second": 32.543,
+    "eval_steps_per_second": 1.017,
+    "train_loss": 4602.791315297503,
+    "train_runtime": 29489.6101,
+    "train_samples": 297394,
+    "train_samples_per_second": 10.085,
+    "train_steps_per_second": 0.158
+}

eval_results.json

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+{
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+    "eval_logits/chosen": -1.583479404449463,
+    "eval_logits/rejected": -1.729608416557312,
+    "eval_logps/chosen": -202.55133056640625,
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+    "eval_loss": 4659.3857421875,
+    "eval_rewards/accuracies": 0.6341965198516846,
+    "eval_rewards/chosen": -0.22735264897346497,
+    "eval_rewards/margins": 0.03718877211213112,
+    "eval_rewards/rejected": -0.2645414173603058,
+    "eval_rewards/safe_rewards": -0.2253904640674591,
+    "eval_rewards/unsafe_rewards": -0.22526215016841888,
+    "eval_runtime": 1015.3903,
+    "eval_samples": 33044,
+    "eval_samples_per_second": 32.543,
+    "eval_steps_per_second": 1.017
+}

generation_config.json

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.36.2"
+}

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train_results.json

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