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_cUNL_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_cUNL_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: 0.5806
+- Sft Loss: 4.6392
+- Rewards/chosen: -4.6683
+- Rewards/rejected: -5.7215
+- Rewards/accuracies: 0.7292
+- Rewards/margins: 1.0533
+- Logps/rejected: -5.7215
+- Logps/chosen: -4.6683
+- Logits/rejected: 0.0927
+- Logits/chosen: 0.0156
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.839         | 0.2141 | 400  | 0.8444          | 1.5362   | -1.7061        | -1.9017          | 0.5564             | 0.1956          | -1.9017        | -1.7061      | 0.3788          | 0.2887        |
+| 0.6224        | 0.4282 | 800  | 0.6288          | 3.4512   | -3.4767        | -4.0245          | 0.6869             | 0.5479          | -4.0245        | -3.4767      | 0.3857          | 0.3092        |
+| 0.6292        | 0.6422 | 1200 | 0.5943          | 3.9913   | -3.8913        | -4.5950          | 0.7211             | 0.7038          | -4.5950        | -3.8913      | 0.3272          | 0.2462        |
+| 0.5282        | 0.8563 | 1600 | 0.5852          | 3.8604   | -3.7994        | -4.4882          | 0.7174             | 0.6888          | -4.4882        | -3.7994      | 0.2184          | 0.1456        |
+| 0.6187        | 1.0704 | 2000 | 0.5858          | 4.1311   | -4.1032        | -4.8789          | 0.7151             | 0.7757          | -4.8789        | -4.1032      | 0.1497          | 0.0695        |
+| 0.5774        | 1.2845 | 2400 | 0.5777          | 4.3179   | -4.2615        | -5.1611          | 0.7277             | 0.8996          | -5.1611        | -4.2615      | 0.2452          | 0.1579        |
+| 0.5393        | 1.4986 | 2800 | 0.5736          | 4.3506   | -4.3258        | -5.2226          | 0.7255             | 0.8968          | -5.2226        | -4.3258      | 0.3460          | 0.2569        |
+| 0.5981        | 1.7127 | 3200 | 0.5695          | 4.2779   | -4.2570        | -5.1734          | 0.7270             | 0.9164          | -5.1734        | -4.2570      | 0.1928          | 0.1184        |
+| 0.5856        | 1.9267 | 3600 | 0.5678          | 4.1129   | -4.0894        | -4.9749          | 0.7337             | 0.8856          | -4.9749        | -4.0894      | 0.1633          | 0.0889        |
+| 0.4692        | 2.1408 | 4000 | 0.5829          | 4.6998   | -4.7020        | -5.7415          | 0.7300             | 1.0395          | -5.7415        | -4.7020      | 0.1569          | 0.0750        |
+| 0.4844        | 2.3549 | 4400 | 0.5827          | 4.6692   | -4.7235        | -5.7762          | 0.7315             | 1.0527          | -5.7762        | -4.7235      | 0.1451          | 0.0641        |
+| 0.488         | 2.5690 | 4800 | 0.5792          | 4.5805   | -4.6213        | -5.6703          | 0.7315             | 1.0490          | -5.6703        | -4.6213      | 0.1281          | 0.0486        |
+| 0.4404        | 2.7831 | 5200 | 0.5804          | 4.6279   | -4.6623        | -5.7139          | 0.7300             | 1.0516          | -5.7139        | -4.6623      | 0.0807          | 0.0044        |
+| 0.4531        | 2.9972 | 5600 | 0.5806          | 4.6392   | -4.6683        | -5.7215          | 0.7292             | 1.0533          | -5.7215        | -4.6683      | 0.0927          | 0.0156        |
+
+
+### 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": 0.5697717436673725,
+    "train_runtime": 31532.5259,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.688,
+    "train_steps_per_second": 0.178
+}

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": 0.5697717436673725,
+    "train_runtime": 31532.5259,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.688,
+    "train_steps_per_second": 0.178
+}