Model save
Browse files- README.md +21 -25
- adapter_config.json +1 -1
- adapter_model.safetensors +1 -1
- all_results.json +16 -16
- eval_results.json +12 -12
- runs/Mar05_10-41-15_gpu4-119-4/events.out.tfevents.1709595839.gpu4-119-4.3155837.0 +3 -0
- runs/Mar05_10-41-15_gpu4-119-4/events.out.tfevents.1709597026.gpu4-119-4.3155837.1 +3 -0
- train_results.json +4 -4
- trainer_state.json +51 -51
- training_args.bin +1 -1
README.md
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license: mit
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library_name: peft
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tags:
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- alignment-handbook
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- generated_from_trainer
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- trl
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- dpo
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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base_model: microsoft/phi-2
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model-index:
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- name: phi-2-gpo-ultrafeedback-lora
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@@ -20,17 +16,17 @@ should probably proofread and complete it, then remove this comment. -->
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# phi-2-gpo-ultrafeedback-lora
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Rewards/chosen: -0.
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- Rewards/rejected: -0.
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- Rewards/accuracies: 0.
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- Rewards/margins: 0.
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- Logps/rejected: -233.
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- Logps/chosen: -261.
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- Logits/rejected: 0.
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- Logits/chosen: 0.
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## Model description
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@@ -65,17 +61,17 @@ The following hyperparameters were used during training:
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### Training results
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| Training Loss | Epoch | Step |
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| 0.0026 | 0.21 | 100 | 0.
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| 0.0023 | 0.42 | 200 | 0.
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| 0.0022 | 0.63 | 300 | 0.
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| 0.0021 | 0.84 | 400 | 0.
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| 0.0022 | 1.05 | 500 | 0.
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| 0.002 | 1.26 | 600 | 0.
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| 0.0021 | 1.47 | 700 | 0.
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| 0.0021 | 1.67 | 800 | 0.
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| 0.0021 | 1.88 | 900 | 0.
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### Framework versions
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license: mit
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library_name: peft
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tags:
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- trl
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- dpo
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- generated_from_trainer
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base_model: microsoft/phi-2
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model-index:
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- name: phi-2-gpo-ultrafeedback-lora
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# phi-2-gpo-ultrafeedback-lora
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0004
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- Rewards/chosen: -0.0084
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- Rewards/rejected: -0.0177
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- Rewards/accuracies: 0.6700
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- Rewards/margins: 0.0093
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- Logps/rejected: -233.2047
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- Logps/chosen: -261.0818
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- Logits/rejected: 0.8824
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- Logits/chosen: 0.7796
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
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|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
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| 0.0026 | 0.21 | 100 | 0.8151 | 0.9175 | -260.2373 | -231.4896 | 0.0025 | 0.5080 | 0.0001 | 0.0006 | -0.0005 |
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| 0.0023 | 0.42 | 200 | 0.8092 | 0.9120 | -260.3932 | -232.1152 | 0.0023 | 0.6560 | -0.0015 | 0.0053 | -0.0068 |
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| 0.0022 | 0.63 | 300 | 0.7992 | 0.9022 | -260.9179 | -232.8447 | 0.0022 | 0.6700 | -0.0067 | 0.0073 | -0.0141 |
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| 0.0021 | 0.84 | 400 | 0.7884 | 0.8914 | -261.1620 | -233.2157 | 0.0022 | 0.6640 | -0.0092 | 0.0086 | -0.0178 |
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| 0.0022 | 1.05 | 500 | 0.7821 | 0.8853 | -261.1852 | -233.3614 | 0.0021 | 0.7100 | -0.0094 | 0.0098 | -0.0193 |
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| 0.002 | 1.26 | 600 | 0.7815 | 0.8840 | -261.1207 | -233.2843 | 0.0021 | 0.6940 | -0.0088 | 0.0097 | -0.0185 |
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| 0.0021 | 1.47 | 700 | 0.7790 | 0.8816 | -261.0788 | -233.2560 | 0.0021 | 0.7000 | -0.0083 | 0.0099 | -0.0182 |
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| 0.0021 | 1.67 | 800 | 0.7781 | 0.8811 | -261.0643 | -233.2740 | 0.0021 | 0.6940 | -0.0082 | 0.0102 | -0.0184 |
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| 0.0021 | 1.88 | 900 | 0.7806 | 0.8833 | -261.0922 | -233.2118 | 0.0021 | 0.6900 | -0.0085 | 0.0093 | -0.0178 |
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### Framework versions
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adapter_config.json
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