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_cpo_entropy_0_3
+  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_cpo_entropy_0_3
+
+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: 1.0436
+- Sft Loss: 1.4855
+- Rewards/chosen: -1.5353
+- Rewards/rejected: -2.2017
+- Rewards/accuracies: 0.6476
+- Rewards/margins: 0.6664
+- Logps/rejected: -2.2017
+- Logps/chosen: -1.5353
+- Logits/rejected: -0.4248
+- Logits/chosen: -0.4735
+
+## 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: 3e-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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 1.0742        | 0.2141 | 400  | 1.0823          | 1.3696   | -1.3461        | -1.5309          | 0.5779             | 0.1848          | -1.5309        | -1.3461      | 0.3537          | 0.2666        |
+| 1.0513        | 0.4282 | 800  | 1.0583          | 1.4056   | -1.4223        | -1.7731          | 0.6039             | 0.3508          | -1.7731        | -1.4223      | 0.2684          | 0.1774        |
+| 1.0763        | 0.6422 | 1200 | 1.0495          | 1.3954   | -1.3876        | -1.7498          | 0.6046             | 0.3622          | -1.7498        | -1.3876      | 0.4388          | 0.3313        |
+| 1.0436        | 0.8563 | 1600 | 1.0524          | 1.3880   | -1.3712        | -1.6780          | 0.6091             | 0.3068          | -1.6780        | -1.3712      | 0.5673          | 0.4476        |
+| 1.0569        | 1.0704 | 2000 | 1.0427          | 1.4160   | -1.4133        | -1.8531          | 0.6298             | 0.4398          | -1.8531        | -1.4133      | 0.0092          | -0.0695       |
+| 0.9655        | 1.2845 | 2400 | 1.0376          | 1.4169   | -1.4205        | -1.9133          | 0.6358             | 0.4928          | -1.9133        | -1.4205      | -0.2668         | -0.3251       |
+| 1.0333        | 1.4986 | 2800 | 1.0458          | 1.3973   | -1.3793        | -1.7731          | 0.6128             | 0.3937          | -1.7731        | -1.3793      | -0.0046         | -0.0841       |
+| 0.9824        | 1.7127 | 3200 | 1.0347          | 1.4063   | -1.3916        | -1.8345          | 0.6283             | 0.4429          | -1.8345        | -1.3916      | -0.2377         | -0.2977       |
+| 0.9557        | 1.9267 | 3600 | 1.0309          | 1.4319   | -1.4343        | -1.9644          | 0.6454             | 0.5301          | -1.9644        | -1.4343      | -0.2903         | -0.3472       |
+| 0.8559        | 2.1408 | 4000 | 1.0420          | 1.4888   | -1.5362        | -2.1635          | 0.6550             | 0.6272          | -2.1635        | -1.5362      | -0.1761         | -0.2434       |
+| 0.8788        | 2.3549 | 4400 | 1.0414          | 1.4794   | -1.5273        | -2.1771          | 0.6469             | 0.6498          | -2.1771        | -1.5273      | -0.2963         | -0.3552       |
+| 0.8747        | 2.5690 | 4800 | 1.0419          | 1.4756   | -1.5253        | -2.1757          | 0.6454             | 0.6504          | -2.1757        | -1.5253      | -0.3952         | -0.4464       |
+| 0.8717        | 2.7831 | 5200 | 1.0438          | 1.4855   | -1.5370        | -2.2063          | 0.6469             | 0.6693          | -2.2063        | -1.5370      | -0.4497         | -0.4964       |
+| 0.8816        | 2.9972 | 5600 | 1.0436          | 1.4855   | -1.5353        | -2.2017          | 0.6476             | 0.6664          | -2.2017        | -1.5353      | -0.4248         | -0.4735       |
+
+
+### 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": 0.9803723535479859,
+    "train_runtime": 32947.1599,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.444,
+    "train_steps_per_second": 0.17
+}

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": 0.9803723535479859,
+    "train_runtime": 32947.1599,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.444,
+    "train_steps_per_second": 0.17
+}