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_uncCPO_entropy_0_01
+  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_uncCPO_entropy_0_01
+
+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: 0.0500
+- Sft Loss: 3.9220
+- Rewards/chosen: -4.3252
+- Rewards/rejected: -5.1044
+- Rewards/accuracies: 0.6892
+- Rewards/margins: 0.7793
+- Logps/rejected: -5.1044
+- Logps/chosen: -4.3252
+- Logits/rejected: 0.1444
+- Logits/chosen: 0.0509
+
+## 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 | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.0563        | 0.2141 | 400  | 0.0573          | 4.8352   | -5.7454        | -6.0246          | 0.5445             | 0.2792          | -6.0246        | -5.7454      | 0.6512          | 0.5372        |
+| 0.0533        | 0.4282 | 800  | 0.0524          | 4.2340   | -4.6954        | -5.0777          | 0.6157             | 0.3823          | -5.0777        | -4.6954      | 0.2939          | 0.1644        |
+| 0.0533        | 0.6422 | 1200 | 0.0518          | 4.1504   | -4.5198        | -5.0186          | 0.6484             | 0.4989          | -5.0186        | -4.5198      | 0.4014          | 0.2684        |
+| 0.0508        | 0.8563 | 1600 | 0.0512          | 4.0690   | -4.5220        | -5.0081          | 0.6491             | 0.4862          | -5.0081        | -4.5220      | 0.2498          | 0.1344        |
+| 0.0529        | 1.0704 | 2000 | 0.0508          | 3.9195   | -4.3917        | -4.9646          | 0.6521             | 0.5729          | -4.9646        | -4.3917      | 0.3268          | 0.2181        |
+| 0.0522        | 1.2845 | 2400 | 0.0504          | 4.1797   | -4.6133        | -5.2771          | 0.6647             | 0.6638          | -5.2771        | -4.6133      | 0.2727          | 0.1622        |
+| 0.0515        | 1.4986 | 2800 | 0.0504          | 4.0933   | -4.4442        | -5.0786          | 0.6825             | 0.6344          | -5.0786        | -4.4442      | 0.2050          | 0.0984        |
+| 0.0526        | 1.7127 | 3200 | 0.0503          | 4.0886   | -4.4943        | -5.1537          | 0.6751             | 0.6594          | -5.1537        | -4.4943      | 0.2002          | 0.0920        |
+| 0.0533        | 1.9267 | 3600 | 0.0501          | 3.9857   | -4.3809        | -5.1003          | 0.6825             | 0.7195          | -5.1003        | -4.3809      | 0.1348          | 0.0421        |
+| 0.0493        | 2.1408 | 4000 | 0.0500          | 3.9751   | -4.3954        | -5.1537          | 0.6840             | 0.7583          | -5.1537        | -4.3954      | 0.3029          | 0.1980        |
+| 0.0522        | 2.3549 | 4400 | 0.0500          | 3.9820   | -4.4013        | -5.1632          | 0.6869             | 0.7619          | -5.1632        | -4.4013      | 0.2139          | 0.1131        |
+| 0.0513        | 2.5690 | 4800 | 0.0500          | 3.9732   | -4.3709        | -5.1160          | 0.6944             | 0.7451          | -5.1160        | -4.3709      | 0.1787          | 0.0785        |
+| 0.0498        | 2.7831 | 5200 | 0.0500          | 3.9372   | -4.3318        | -5.0969          | 0.6892             | 0.7651          | -5.0969        | -4.3318      | 0.2138          | 0.1134        |
+| 0.0496        | 2.9972 | 5600 | 0.0500          | 3.9220   | -4.3252        | -5.1044          | 0.6892             | 0.7793          | -5.1044        | -4.3252      | 0.1444          | 0.0509        |
+
+
+### 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": 0.05868237358195538,
+    "train_runtime": 34511.7277,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.197,
+    "train_steps_per_second": 0.162
+}

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": 0.05868237358195538,
+    "train_runtime": 34511.7277,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.197,
+    "train_steps_per_second": 0.162
+}