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_ce_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_ce_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: 1.6698
+- Rewards/chosen: -1.2671
+- Rewards/rejected: -1.4042
+- Rewards/accuracies: 0.5475
+- Rewards/margins: 0.1371
+- Logps/rejected: -1.4042
+- Logps/chosen: -1.2671
+- Logits/rejected: 0.0682
+- Logits/chosen: 0.0048
+- Semantic Entropy: 0.8052
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------------:|
+| 1.6978        | 0.2141 | 400  | 1.7217          | -1.3251        | -1.4461          | 0.5542             | 0.1210          | -1.4461        | -1.3251      | 0.3247          | 0.2440        | 0.7926           |
+| 1.6742        | 0.4282 | 800  | 1.6949          | -1.2943        | -1.4240          | 0.5512             | 0.1298          | -1.4240        | -1.2943      | 0.3049          | 0.2297        | 0.8009           |
+| 1.6257        | 0.6422 | 1200 | 1.6872          | -1.2855        | -1.4133          | 0.5497             | 0.1277          | -1.4133        | -1.2855      | 0.3184          | 0.2421        | 0.8030           |
+| 1.6968        | 0.8563 | 1600 | 1.6820          | -1.2796        | -1.4093          | 0.5497             | 0.1297          | -1.4093        | -1.2796      | 0.2761          | 0.2028        | 0.8045           |
+| 1.6822        | 1.0704 | 2000 | 1.6787          | -1.2761        | -1.4082          | 0.5475             | 0.1321          | -1.4082        | -1.2761      | 0.2216          | 0.1509        | 0.8049           |
+| 1.6094        | 1.2845 | 2400 | 1.6751          | -1.2721        | -1.4072          | 0.5512             | 0.1351          | -1.4072        | -1.2721      | 0.1377          | 0.0723        | 0.8058           |
+| 1.6739        | 1.4986 | 2800 | 1.6730          | -1.2698        | -1.4034          | 0.5497             | 0.1336          | -1.4034        | -1.2698      | 0.2715          | 0.1954        | 0.8061           |
+| 1.6298        | 1.7127 | 3200 | 1.6720          | -1.2684        | -1.4016          | 0.5482             | 0.1333          | -1.4016        | -1.2684      | 0.2307          | 0.1571        | 0.8069           |
+| 1.5782        | 1.9267 | 3600 | 1.6708          | -1.2674        | -1.4010          | 0.5475             | 0.1337          | -1.4010        | -1.2674      | 0.1038          | 0.0385        | 0.8067           |
+| 1.5741        | 2.1408 | 4000 | 1.6708          | -1.2680        | -1.4049          | 0.5497             | 0.1369          | -1.4049        | -1.2680      | 0.1744          | 0.1034        | 0.8055           |
+| 1.5681        | 2.3549 | 4400 | 1.6702          | -1.2675        | -1.4043          | 0.5475             | 0.1369          | -1.4043        | -1.2675      | 0.1310          | 0.0627        | 0.8052           |
+| 1.5524        | 2.5690 | 4800 | 1.6700          | -1.2673        | -1.4043          | 0.5482             | 0.1370          | -1.4043        | -1.2673      | 0.0834          | 0.0188        | 0.8053           |
+| 1.537         | 2.7831 | 5200 | 1.6700          | -1.2672        | -1.4043          | 0.5482             | 0.1371          | -1.4043        | -1.2672      | 0.0930          | 0.0277        | 0.8053           |
+| 1.5699        | 2.9972 | 5600 | 1.6698          | -1.2671        | -1.4042          | 0.5475             | 0.1371          | -1.4042        | -1.2671      | 0.0682          | 0.0048        | 0.8052           |
+
+
+### 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": 1.640899122824931,
+    "train_runtime": 28500.0022,
+    "train_samples": 59790,
+    "train_samples_per_second": 6.294,
+    "train_steps_per_second": 0.197
+}

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": 1.640899122824931,
+    "train_runtime": 28500.0022,
+    "train_samples": 59790,
+    "train_samples_per_second": 6.294,
+    "train_steps_per_second": 0.197
+}