Model save

README.md

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+---
+library_name: transformers
+license: other
+base_model: trl-lib/qwen1.5-0.5b-sft
+tags:
+- trl
+- simpo
+- generated_from_trainer
+model-index:
+- name: qwen_orpo_entropy
+  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. -->
+
+# qwen_orpo_entropy
+
+This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5245
+- Rewards/chosen: -9.9757
+- Rewards/rejected: -11.1054
+- Rewards/accuracies: 0.7240
+- Rewards/margins: 1.1296
+- Logps/rejected: -11.1054
+- Logps/chosen: -9.9757
+- Logits/rejected: 0.9577
+- Logits/chosen: 0.9163
+- Semantic Entropy: 0.0013
+
+## 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: 1e-06
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 16
+- total_train_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: 3.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Semantic Entropy |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------------:|
+| 1.0119        | 0.2141 | 400  | 1.0132          | -1.7930        | -2.0280          | 0.5660             | 0.2350          | -2.0280        | -1.7930      | 0.3600          | 0.2738        | 0.6132           |
+| 0.5924        | 0.4282 | 800  | 0.5851          | -6.7409        | -7.2987          | 0.6810             | 0.5578          | -7.2987        | -6.7409      | 0.5386          | 0.4884        | 0.0131           |
+| 0.5951        | 0.6422 | 1200 | 0.5522          | -7.9883        | -8.6813          | 0.7062             | 0.6931          | -8.6813        | -7.9883      | 0.7969          | 0.7507        | 0.0050           |
+| 0.4796        | 0.8563 | 1600 | 0.5406          | -8.4790        | -9.1974          | 0.7047             | 0.7184          | -9.1974        | -8.4790      | 0.9158          | 0.8517        | 0.0035           |
+| 0.5834        | 1.0704 | 2000 | 0.5344          | -8.7256        | -9.5131          | 0.7159             | 0.7875          | -9.5131        | -8.7256      | 0.8620          | 0.7784        | 0.0027           |
+| 0.5261        | 1.2845 | 2400 | 0.5313          | -8.7103        | -9.6511          | 0.7136             | 0.9408          | -9.6511        | -8.7103      | 0.8723          | 0.8012        | 0.0029           |
+| 0.4879        | 1.4986 | 2800 | 0.5264          | -8.6267        | -9.5330          | 0.7218             | 0.9063          | -9.5330        | -8.6267      | 0.7496          | 0.6896        | 0.0033           |
+| 0.5524        | 1.7127 | 3200 | 0.5207          | -8.8757        | -9.8346          | 0.7166             | 0.9589          | -9.8346        | -8.8757      | 0.9052          | 0.8485        | 0.0030           |
+| 0.5311        | 1.9267 | 3600 | 0.5170          | -9.0983        | -10.0747         | 0.7233             | 0.9765          | -10.0747       | -9.0983      | 0.8342          | 0.7884        | 0.0024           |
+| 0.3953        | 2.1408 | 4000 | 0.5261          | -9.8407        | -10.9409         | 0.7196             | 1.1002          | -10.9409       | -9.8407      | 0.9782          | 0.9286        | 0.0015           |
+| 0.428         | 2.3549 | 4400 | 0.5250          | -9.9515        | -11.0890         | 0.7211             | 1.1375          | -11.0890       | -9.9515      | 0.9721          | 0.9215        | 0.0013           |
+| 0.4394        | 2.5690 | 4800 | 0.5238          | -9.8173        | -10.9421         | 0.7255             | 1.1248          | -10.9421       | -9.8173      | 0.8956          | 0.8550        | 0.0014           |
+| 0.4221        | 2.7831 | 5200 | 0.5239          | -9.9581        | -11.0861         | 0.7248             | 1.1280          | -11.0861       | -9.9581      | 0.9048          | 0.8672        | 0.0013           |
+| 0.4023        | 2.9972 | 5600 | 0.5245          | -9.9757        | -11.1054         | 0.7240             | 1.1296          | -11.1054       | -9.9757      | 0.9577          | 0.9163        | 0.0013           |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 2.999297541394882,
+    "total_flos": 0.0,
+    "train_loss": 0.5450739759491819,
+    "train_runtime": 29046.9509,
+    "train_samples": 59790,
+    "train_samples_per_second": 6.175,
+    "train_steps_per_second": 0.193
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.44.2"
+}

train_results.json

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+{
+    "epoch": 2.999297541394882,
+    "total_flos": 0.0,
+    "train_loss": 0.5450739759491819,
+    "train_runtime": 29046.9509,
+    "train_samples": 59790,
+    "train_samples_per_second": 6.175,
+    "train_steps_per_second": 0.193
+}