Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: alignment-handbook/zephyr-7b-sft-full
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: zephyr-7b-uf-rlced-conifer-group-dpo-2e
+  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. -->
+
+# zephyr-7b-uf-rlced-conifer-group-dpo-2e
+
+This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2410
+- Rewards/chosen: -3.4515
+- Rewards/rejected: -8.7505
+- Rewards/accuracies: 0.8769
+- Rewards/margins: 5.2990
+- Logps/rejected: -1278.7848
+- Logps/chosen: -737.6204
+- Logits/rejected: 3.0507
+- Logits/chosen: 0.9407
+- Alpha0: 0.6369
+- Alpha1: 0.3631
+- Task Loss1: 0.1726
+- Task Excess Loss1: 0.0379
+- Excess Loss: 0.0341
+- Task Loss0: 0.5306
+- Task Excess Loss0: 0.0889
+
+## 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: 5e-07
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Alpha0 | Alpha1 | Task Loss1 | Task Excess Loss1 | Excess Loss | Task Loss0 | Task Excess Loss0 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:------:|:------:|:----------:|:-----------------:|:-----------:|:----------:|:-----------------:|
+| 0.3541        | 0.1388 | 100  | 0.4194          | -1.3743        | -2.6267          | 0.8102             | 1.2524          | -666.4093      | -529.9026    | -2.7580         | -2.7843       | 0.8214 | 0.1786 | 0.3373     | 0.1973            | 0.1899      | 0.6883     | 0.2655            |
+| 0.2214        | 0.2776 | 200  | 0.3480          | -1.2450        | -2.9488          | 0.8412             | 1.7038          | -698.6146      | -516.9692    | 0.1216          | -0.2174       | 0.8786 | 0.1214 | 0.2866     | 0.1517            | 0.1250      | 0.5355     | 0.0929            |
+| 0.2284        | 0.4164 | 300  | 0.3271          | -1.7298        | -3.6279          | 0.8515             | 1.8981          | -766.5247      | -565.4502    | 1.3769          | 0.5823        | 0.6417 | 0.3583 | 0.2721     | 0.1383            | 0.1130      | 0.5406     | 0.0794            |
+| 0.1837        | 0.5552 | 400  | 0.3040          | -1.7232        | -4.0037          | 0.8553             | 2.2805          | -804.1021      | -564.7872    | 1.8300          | 0.7862        | 0.7891 | 0.2109 | 0.2517     | 0.1159            | 0.0949      | 0.5490     | 0.0796            |
+| 0.1749        | 0.6940 | 500  | 0.2966          | -1.7976        | -4.1927          | 0.8637             | 2.3951          | -823.0039      | -572.2305    | 1.7164          | 0.5785        | 0.8057 | 0.1943 | 0.2448     | 0.1097            | 0.0856      | 0.5124     | 0.0570            |
+| 0.1823        | 0.8328 | 600  | 0.3030          | -1.7187        | -3.9261          | 0.8647             | 2.2074          | -796.3432      | -564.3366    | 2.4921          | 1.3988        | 0.9053 | 0.0947 | 0.2541     | 0.1193            | 0.0922      | 0.5047     | 0.0596            |
+| 0.1766        | 0.9715 | 700  | 0.2895          | -1.6400        | -4.2369          | 0.8647             | 2.5969          | -827.4293      | -556.4711    | 1.6749          | 0.1680        | 0.9622 | 0.0378 | 0.2417     | 0.1057            | 0.0812      | 0.5020     | 0.0532            |
+| 0.1131        | 1.1103 | 800  | 0.2646          | -2.7794        | -6.7040          | 0.8647             | 3.9245          | -1074.1326     | -670.4117    | 2.3249          | 0.3844        | 0.0325 | 0.9675 | 0.1990     | 0.0653            | 0.0567      | 0.5372     | 0.0871            |
+| 0.1006        | 1.2491 | 900  | 0.2490          | -3.6465        | -8.6692          | 0.8712             | 5.0227          | -1270.6554     | -757.1147    | 3.3211          | 1.0777        | 0.4760 | 0.5240 | 0.1852     | 0.0492            | 0.0420      | 0.5341     | 0.0967            |
+| 0.0951        | 1.3879 | 1000 | 0.2470          | -3.0354        | -7.7369          | 0.8797             | 4.7015          | -1177.4214     | -696.0082    | 3.1614          | 0.9199        | 0.0150 | 0.9850 | 0.1756     | 0.0450            | 0.0382      | 0.5249     | 0.0834            |
+| 0.0885        | 1.5267 | 1100 | 0.2435          | -3.4543        | -8.4740          | 0.8731             | 5.0197          | -1251.1321     | -737.8961    | 3.4589          | 1.3892        | 0.0151 | 0.9849 | 0.1747     | 0.0421            | 0.0368      | 0.5310     | 0.0887            |
+| 0.1003        | 1.6655 | 1200 | 0.2416          | -3.3615        | -8.4285          | 0.875              | 5.0670          | -1246.5889     | -728.6184    | 2.9341          | 0.9100        | 0.0721 | 0.9279 | 0.1730     | 0.0396            | 0.0352      | 0.5285     | 0.0863            |
+| 0.0865        | 1.8043 | 1300 | 0.2412          | -3.3114        | -8.4737          | 0.8769             | 5.1623          | -1251.1091     | -723.6140    | 2.9432          | 0.8628        | 0.0755 | 0.9245 | 0.1734     | 0.0388            | 0.0343      | 0.5272     | 0.0847            |
+| 0.0893        | 1.9431 | 1400 | 0.2410          | -3.4515        | -8.7505          | 0.8769             | 5.2990          | -1278.7848     | -737.6204    | 3.0507          | 0.9407        | 0.6369 | 0.3631 | 0.1726     | 0.0379            | 0.0341      | 0.5306     | 0.0889            |
+
+
+### Framework versions
+
+- Transformers 4.44.1
+- Pytorch 2.1.2+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 1.9986120749479528,
+    "total_flos": 0.0,
+    "train_loss": 0.17575526105033026,
+    "train_runtime": 46867.94,
+    "train_samples": 184443,
+    "train_samples_per_second": 7.871,
+    "train_steps_per_second": 0.031
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.44.1"
+}

train_results.json

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+{
+    "epoch": 1.9986120749479528,
+    "total_flos": 0.0,
+    "train_loss": 0.17575526105033026,
+    "train_runtime": 46867.94,
+    "train_samples": 184443,
+    "train_samples_per_second": 7.871,
+    "train_steps_per_second": 0.031
+}