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_qfUNL_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_qfUNL_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: 0.6685
+- Sft Loss: 1.5897
+- Rewards/chosen: -1.6017
+- Rewards/rejected: -2.2330
+- Rewards/accuracies: 0.6506
+- Rewards/margins: 0.6314
+- Logps/rejected: -2.2330
+- Logps/chosen: -1.6017
+- Logits/rejected: 0.2142
+- Logits/chosen: 0.1178
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6889        | 0.2141 | 400  | 0.7003          | 1.4382   | -1.5229        | -1.6955          | 0.5579             | 0.1726          | -1.6955        | -1.5229      | 0.2817          | 0.1945        |
+| 0.6916        | 0.4282 | 800  | 0.6822          | 1.5282   | -1.5414        | -1.8469          | 0.6076             | 0.3055          | -1.8469        | -1.5414      | 0.2875          | 0.2001        |
+| 0.6757        | 0.6422 | 1200 | 0.6771          | 1.5574   | -1.5600        | -1.9539          | 0.6217             | 0.3939          | -1.9539        | -1.5600      | 0.2922          | 0.2043        |
+| 0.6744        | 0.8563 | 1600 | 0.6739          | 1.5959   | -1.6093        | -2.0408          | 0.6335             | 0.4315          | -2.0408        | -1.6093      | 0.2827          | 0.1913        |
+| 0.714         | 1.0704 | 2000 | 0.6719          | 1.5564   | -1.5625        | -2.0466          | 0.6269             | 0.4841          | -2.0466        | -1.5625      | 0.1990          | 0.1104        |
+| 0.6715        | 1.2845 | 2400 | 0.6719          | 1.5799   | -1.5845        | -2.1083          | 0.6380             | 0.5238          | -2.1083        | -1.5845      | 0.2487          | 0.1536        |
+| 0.6658        | 1.4986 | 2800 | 0.6707          | 1.6055   | -1.6197        | -2.1818          | 0.6454             | 0.5621          | -2.1818        | -1.6197      | 0.1108          | 0.0257        |
+| 0.6709        | 1.7127 | 3200 | 0.6701          | 1.5845   | -1.5941        | -2.1721          | 0.6476             | 0.5780          | -2.1721        | -1.5941      | 0.1373          | 0.0502        |
+| 0.659         | 1.9267 | 3600 | 0.6686          | 1.5568   | -1.5549        | -2.1383          | 0.6454             | 0.5835          | -2.1383        | -1.5549      | 0.1189          | 0.0332        |
+| 0.6241        | 2.1408 | 4000 | 0.6689          | 1.5859   | -1.5837        | -2.1770          | 0.6454             | 0.5933          | -2.1770        | -1.5837      | 0.1840          | 0.0917        |
+| 0.6443        | 2.3549 | 4400 | 0.6692          | 1.5919   | -1.6001        | -2.2168          | 0.6461             | 0.6166          | -2.2168        | -1.6001      | 0.0426          | -0.0398       |
+| 0.6356        | 2.5690 | 4800 | 0.6686          | 1.5864   | -1.5964        | -2.2216          | 0.6484             | 0.6252          | -2.2216        | -1.5964      | 0.1106          | 0.0226        |
+| 0.6448        | 2.7831 | 5200 | 0.6683          | 1.5882   | -1.5994        | -2.2308          | 0.6506             | 0.6314          | -2.2308        | -1.5994      | 0.0974          | 0.0105        |
+| 0.6368        | 2.9972 | 5600 | 0.6685          | 1.5897   | -1.6017        | -2.2330          | 0.6506             | 0.6314          | -2.2330        | -1.6017      | 0.2142          | 0.1178        |
+
+
+### 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": 0.6685084665272595,
+    "train_runtime": 33774.3849,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.311,
+    "train_steps_per_second": 0.166
+}

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": 0.6685084665272595,
+    "train_runtime": 33774.3849,
+    "train_samples": 59790,
+    "train_samples_per_second": 5.311,
+    "train_steps_per_second": 0.166
+}