Model save

README.md

@@ -0,0 +1,86 @@
+---
+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_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_cCPO_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: 0.4896
+- Sft Loss: 1.6913
+- Rewards/chosen: -1.6159
+- Rewards/rejected: -2.1942
+- Rewards/accuracies: 0.6714
+- Rewards/margins: 0.5783
+- Logps/rejected: -2.1942
+- Logps/chosen: -1.6159
+- Logits/rejected: 0.2372
+- Logits/chosen: 0.1346
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.5602        | 0.2141 | 400  | 0.5593          | 1.3702   | -1.3432        | -1.4801          | 0.5579             | 0.1369          | -1.4801        | -1.3432      | 0.3397          | 0.2525        |
+| 0.5448        | 0.4282 | 800  | 0.5318          | 1.4044   | -1.3785        | -1.6209          | 0.5883             | 0.2424          | -1.6209        | -1.3785      | 0.3618          | 0.2727        |
+| 0.5415        | 0.6422 | 1200 | 0.5156          | 1.4648   | -1.4398        | -1.7890          | 0.6187             | 0.3493          | -1.7890        | -1.4398      | 0.3220          | 0.2312        |
+| 0.4953        | 0.8563 | 1600 | 0.5101          | 1.4980   | -1.4449        | -1.7958          | 0.6261             | 0.3509          | -1.7958        | -1.4449      | 0.3743          | 0.2752        |
+| 0.5743        | 1.0704 | 2000 | 0.5047          | 1.4884   | -1.4330        | -1.8072          | 0.6306             | 0.3742          | -1.8072        | -1.4330      | 0.3107          | 0.2131        |
+| 0.4824        | 1.2845 | 2400 | 0.4963          | 1.6007   | -1.5341        | -2.0179          | 0.6536             | 0.4838          | -2.0179        | -1.5341      | 0.3099          | 0.2106        |
+| 0.5266        | 1.4986 | 2800 | 0.4947          | 1.6155   | -1.5391        | -2.0193          | 0.6573             | 0.4801          | -2.0193        | -1.5391      | 0.2939          | 0.1953        |
+| 0.5053        | 1.7127 | 3200 | 0.4936          | 1.5759   | -1.5037        | -1.9595          | 0.6484             | 0.4558          | -1.9595        | -1.5037      | 0.3131          | 0.2133        |
+| 0.4712        | 1.9267 | 3600 | 0.4894          | 1.6467   | -1.5640        | -2.0770          | 0.6662             | 0.5129          | -2.0770        | -1.5640      | 0.3113          | 0.2089        |
+| 0.4297        | 2.1408 | 4000 | 0.4894          | 1.6624   | -1.5827        | -2.1264          | 0.6699             | 0.5437          | -2.1264        | -1.5827      | 0.2311          | 0.1311        |
+| 0.4418        | 2.3549 | 4400 | 0.4909          | 1.7121   | -1.6395        | -2.2277          | 0.6736             | 0.5882          | -2.2277        | -1.6395      | 0.2582          | 0.1535        |
+| 0.4422        | 2.5690 | 4800 | 0.4894          | 1.6890   | -1.6151        | -2.1880          | 0.6699             | 0.5729          | -2.1880        | -1.6151      | 0.2371          | 0.1340        |
+| 0.4463        | 2.7831 | 5200 | 0.4895          | 1.6851   | -1.6106        | -2.1856          | 0.6706             | 0.5751          | -2.1856        | -1.6106      | 0.2327          | 0.1306        |
+| 0.4311        | 2.9972 | 5600 | 0.4896          | 1.6913   | -1.6159        | -2.1942          | 0.6714             | 0.5783          | -2.1942        | -1.6159      | 0.2372          | 0.1346        |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

all_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 2.999297541394882,
+    "total_flos": 0.0,
+    "train_loss": 0.49661777635968474,
+    "train_runtime": 31536.5493,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.688,
+    "train_steps_per_second": 0.178
+}

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.44.2"
+}

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 2.999297541394882,
+    "total_flos": 0.0,
+    "train_loss": 0.49661777635968474,
+    "train_runtime": 31536.5493,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.688,
+    "train_steps_per_second": 0.178
+}