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_l21_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_l21_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: 0.6901
+- Sft Loss: 2.1331
+- Rewards/chosen: -2.1707
+- Rewards/rejected: -3.2271
+- Rewards/accuracies: 0.6914
+- Rewards/margins: 1.0563
+- Logps/rejected: -3.2271
+- Logps/chosen: -2.1707
+- Logits/rejected: 0.2151
+- Logits/chosen: 0.1185
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.7149        | 0.2141 | 400  | 0.7232          | 2.1337   | -3.3125        | -3.5682          | 0.5200             | 0.2557          | -3.5682        | -3.3125      | 0.5534          | 0.4407        |
+| 0.7105        | 0.4282 | 800  | 0.7055          | 2.1066   | -2.2353        | -2.7243          | 0.6447             | 0.4890          | -2.7243        | -2.2353      | 0.3870          | 0.2857        |
+| 0.7071        | 0.6422 | 1200 | 0.6988          | 2.0445   | -2.1363        | -2.7640          | 0.6691             | 0.6278          | -2.7640        | -2.1363      | 0.6763          | 0.5552        |
+| 0.6909        | 0.8563 | 1600 | 0.6951          | 2.2316   | -2.3067        | -3.0785          | 0.6825             | 0.7718          | -3.0785        | -2.3067      | 0.0414          | -0.0345       |
+| 0.6992        | 1.0704 | 2000 | 0.6927          | 2.0672   | -2.1384        | -2.9634          | 0.6766             | 0.8250          | -2.9634        | -2.1384      | 0.1253          | 0.0374        |
+| 0.6894        | 1.2845 | 2400 | 0.6908          | 2.1132   | -2.1527        | -3.0987          | 0.6810             | 0.9460          | -3.0987        | -2.1527      | 0.3470          | 0.2424        |
+| 0.6881        | 1.4986 | 2800 | 0.6908          | 2.1384   | -2.2307        | -3.1888          | 0.6862             | 0.9581          | -3.1888        | -2.2307      | 0.5238          | 0.4064        |
+| 0.6998        | 1.7127 | 3200 | 0.6900          | 2.1093   | -2.1719        | -3.1258          | 0.6936             | 0.9539          | -3.1258        | -2.1719      | 0.2688          | 0.1694        |
+| 0.6837        | 1.9267 | 3600 | 0.6898          | 2.1422   | -2.2075        | -3.2094          | 0.6966             | 1.0019          | -3.2094        | -2.2075      | 0.3036          | 0.1996        |
+| 0.6446        | 2.1408 | 4000 | 0.6902          | 2.1614   | -2.1867        | -3.2140          | 0.6855             | 1.0273          | -3.2140        | -2.1867      | 0.2205          | 0.1222        |
+| 0.6694        | 2.3549 | 4400 | 0.6887          | 2.1145   | -2.1590        | -3.1865          | 0.6921             | 1.0275          | -3.1865        | -2.1590      | 0.2474          | 0.1483        |
+| 0.6722        | 2.5690 | 4800 | 0.6902          | 2.1289   | -2.1610        | -3.2026          | 0.6907             | 1.0415          | -3.2026        | -2.1610      | 0.2232          | 0.1258        |
+| 0.6701        | 2.7831 | 5200 | 0.6904          | 2.1329   | -2.1699        | -3.2263          | 0.6929             | 1.0564          | -3.2263        | -2.1699      | 0.2407          | 0.1420        |
+| 0.659         | 2.9972 | 5600 | 0.6901          | 2.1331   | -2.1707        | -3.2271          | 0.6914             | 1.0563          | -3.2271        | -2.1707      | 0.2151          | 0.1185        |
+
+
+### 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": 0.6914210148065283,
+    "train_runtime": 33926.4655,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.287,
+    "train_steps_per_second": 0.165
+}

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": 0.6914210148065283,
+    "train_runtime": 33926.4655,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.287,
+    "train_steps_per_second": 0.165
+}