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_cCPO_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_cCPO_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: 0.5210
+- Rewards/chosen: -9.5408
+- Rewards/rejected: -10.6523
+- Rewards/accuracies: 0.7166
+- Rewards/margins: 1.1115
+- Logps/rejected: -10.6523
+- Logps/chosen: -9.5408
+- Logits/rejected: 0.4143
+- Logits/chosen: 0.3542
+- Semantic Entropy: 0.0025
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------------:|
+| 0.9273        | 0.2141 | 400  | 0.9132          | -1.5626        | -1.7709          | 0.5727             | 0.2083          | -1.7709        | -1.5626      | 0.3591          | 0.2698        | 0.6963           |
+| 0.6005        | 0.4282 | 800  | 0.5930          | -6.2110        | -6.7875          | 0.6714             | 0.5765          | -6.7875        | -6.2110      | 0.0273          | -0.0585       | 0.0266           |
+| 0.5591        | 0.6422 | 1200 | 0.5548          | -8.0914        | -8.7875          | 0.6936             | 0.6960          | -8.7875        | -8.0914      | 0.0627          | -0.0250       | 0.0053           |
+| 0.4839        | 0.8563 | 1600 | 0.5401          | -8.0351        | -8.7538          | 0.7092             | 0.7187          | -8.7538        | -8.0351      | 0.1712          | 0.0772        | 0.0055           |
+| 0.5873        | 1.0704 | 2000 | 0.5368          | -8.3578        | -9.1522          | 0.7114             | 0.7944          | -9.1522        | -8.3578      | 0.1990          | 0.1107        | 0.0039           |
+| 0.5089        | 1.2845 | 2400 | 0.5257          | -8.4730        | -9.4241          | 0.7211             | 0.9510          | -9.4241        | -8.4730      | 0.1623          | 0.0831        | 0.0047           |
+| 0.5109        | 1.4986 | 2800 | 0.5215          | -8.6140        | -9.5173          | 0.7263             | 0.9033          | -9.5173        | -8.6140      | 0.2671          | 0.1852        | 0.0039           |
+| 0.5508        | 1.7127 | 3200 | 0.5167          | -8.8251        | -9.7884          | 0.7277             | 0.9633          | -9.7884        | -8.8251      | 0.3885          | 0.3079        | 0.0035           |
+| 0.5684        | 1.9267 | 3600 | 0.5155          | -8.8490        | -9.8374          | 0.7240             | 0.9884          | -9.8374        | -8.8490      | 0.3563          | 0.2827        | 0.0032           |
+| 0.4288        | 2.1408 | 4000 | 0.5242          | -9.3271        | -10.4242         | 0.7211             | 1.0971          | -10.4242       | -9.3271      | 0.4923          | 0.4276        | 0.0026           |
+| 0.4556        | 2.3549 | 4400 | 0.5198          | -9.5864        | -10.6863         | 0.7203             | 1.0999          | -10.6863       | -9.5864      | 0.4365          | 0.3746        | 0.0024           |
+| 0.4621        | 2.5690 | 4800 | 0.5210          | -9.4722        | -10.5759         | 0.7196             | 1.1037          | -10.5759       | -9.4722      | 0.4038          | 0.3433        | 0.0026           |
+| 0.4387        | 2.7831 | 5200 | 0.5208          | -9.5239        | -10.6317         | 0.7181             | 1.1079          | -10.6317       | -9.5239      | 0.3872          | 0.3286        | 0.0025           |
+| 0.4041        | 2.9972 | 5600 | 0.5210          | -9.5408        | -10.6523         | 0.7166             | 1.1115          | -10.6523       | -9.5408      | 0.4143          | 0.3542        | 0.0025           |
+
+
+### 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": 0.5415812020936581,
+    "train_runtime": 28601.8206,
+    "train_samples": 59790,
+    "train_samples_per_second": 6.271,
+    "train_steps_per_second": 0.196
+}

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": 0.5415812020936581,
+    "train_runtime": 28601.8206,
+    "train_samples": 59790,
+    "train_samples_per_second": 6.271,
+    "train_steps_per_second": 0.196
+}