Model save

README.md

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+---
+library_name: transformers
+license: other
+base_model: flydust/Llama-3.1-Minitron-4B-Magpie-Gemma2-9B-550K
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: Llama-3.1-Minitron-4B-Magpie-SFT-G550K-MT-Magpo-3.1-Pro-015Mix
+  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-3.1-Minitron-4B-Magpie-SFT-G550K-MT-Magpo-3.1-Pro-015Mix
+
+This model is a fine-tuned version of [flydust/Llama-3.1-Minitron-4B-Magpie-Gemma2-9B-550K](https://huggingface.co/flydust/Llama-3.1-Minitron-4B-Magpie-Gemma2-9B-550K) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4942
+- Rewards/chosen: -3.3377
+- Rewards/rejected: -4.2603
+- Rewards/accuracies: 0.7620
+- Rewards/margins: 0.9226
+- Logps/rejected: -928.2655
+- Logps/chosen: -844.1144
+- Logits/rejected: -1.4591
+- Logits/chosen: -1.4783
+
+## 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: 1.5e-07
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 16
+- 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 | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6911        | 0.0653 | 100  | 0.6912          | -0.0026        | -0.0066          | 0.5640             | 0.0041          | -502.9037      | -510.6042    | -1.7834         | -1.7781       |
+| 0.6703        | 0.1306 | 200  | 0.6713          | -0.1429        | -0.1981          | 0.6380             | 0.0552          | -522.0521      | -524.6394    | -1.7686         | -1.7593       |
+| 0.6306        | 0.1959 | 300  | 0.6347          | -0.6439        | -0.8210          | 0.6840             | 0.1770          | -584.3356      | -574.7375    | -1.7536         | -1.7436       |
+| 0.5831        | 0.2612 | 400  | 0.5932          | -1.5155        | -1.8774          | 0.7070             | 0.3619          | -689.9788      | -661.8920    | -1.6963         | -1.6877       |
+| 0.5447        | 0.3266 | 500  | 0.5645          | -2.1858        | -2.7052          | 0.7110             | 0.5195          | -772.7636      | -728.9221    | -1.6249         | -1.6207       |
+| 0.5896        | 0.3919 | 600  | 0.5453          | -2.3771        | -2.9747          | 0.7180             | 0.5976          | -799.7122      | -748.0584    | -1.5836         | -1.5847       |
+| 0.5342        | 0.4572 | 700  | 0.5305          | -2.6231        | -3.3063          | 0.7350             | 0.6832          | -832.8744      | -772.6592    | -1.5454         | -1.5524       |
+| 0.511         | 0.5225 | 800  | 0.5177          | -3.0517        | -3.8393          | 0.7400             | 0.7876          | -886.1714      | -815.5145    | -1.5160         | -1.5273       |
+| 0.5007        | 0.5878 | 900  | 0.5088          | -3.0925        | -3.9197          | 0.7540             | 0.8273          | -894.2120      | -819.5908    | -1.5007         | -1.5144       |
+| 0.485         | 0.6531 | 1000 | 0.5033          | -3.1305        | -3.9863          | 0.7630             | 0.8558          | -900.8680      | -823.3940    | -1.4834         | -1.4997       |
+| 0.4307        | 0.7184 | 1100 | 0.4989          | -3.1387        | -4.0097          | 0.7610             | 0.8710          | -903.2113      | -824.2159    | -1.4728         | -1.4911       |
+| 0.5403        | 0.7837 | 1200 | 0.4964          | -3.3418        | -4.2574          | 0.7620             | 0.9156          | -927.9747      | -844.5242    | -1.4641         | -1.4822       |
+| 0.5182        | 0.8490 | 1300 | 0.4952          | -3.3255        | -4.2430          | 0.7600             | 0.9175          | -926.5396      | -842.8945    | -1.4601         | -1.4788       |
+| 0.5165        | 0.9144 | 1400 | 0.4943          | -3.3308        | -4.2525          | 0.7600             | 0.9217          | -927.4913      | -843.4282    | -1.4610         | -1.4799       |
+| 0.5192        | 0.9797 | 1500 | 0.4942          | -3.3377        | -4.2603          | 0.7620             | 0.9226          | -928.2655      | -844.1144    | -1.4591         | -1.4783       |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 0.9999183606825047,
+    "total_flos": 0.0,
+    "train_loss": 0.5524635882372952,
+    "train_runtime": 40329.8241,
+    "train_samples": 195977,
+    "train_samples_per_second": 4.859,
+    "train_steps_per_second": 0.038
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": 128001,
+  "transformers_version": "4.45.0.dev0"
+}

train_results.json

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+{
+    "epoch": 0.9999183606825047,
+    "total_flos": 0.0,
+    "train_loss": 0.5524635882372952,
+    "train_runtime": 40329.8241,
+    "train_samples": 195977,
+    "train_samples_per_second": 4.859,
+    "train_steps_per_second": 0.038
+}