Model save
Browse files- .gitattributes +1 -0
- README.md +73 -0
- all_results.json +9 -0
- config.json +29 -0
- generation_config.json +7 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
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- model.safetensors.index.json +261 -0
- runs/Apr27_16-40-45_660111d13776/events.out.tfevents.1714232555.660111d13776.64926.0 +3 -0
- special_tokens_map.json +34 -0
- tokenizer.json +3 -0
- tokenizer_config.json +70 -0
- train_results.json +9 -0
- trainer_state.json +211 -0
- training_args.bin +3 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: other
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base_model: HuggingFaceH4/zephyr-7b-gemma-sft-v0.1
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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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model-index:
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- name: zephyr-7b-gemma-hinge
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# zephyr-7b-gemma-hinge
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This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-gemma-sft-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-sft-v0.1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5250
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- Rewards/chosen: -2.6386
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- Rewards/rejected: -3.9001
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- Rewards/accuracies: 0.7188
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- Rewards/margins: 1.2616
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- Logps/rejected: -440.0739
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- Logps/chosen: -416.4398
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- Logits/rejected: 95.9739
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- Logits/chosen: 101.8169
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 2
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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| 0.1516 | 1.8957 | 100 | 0.5250 | -2.6386 | -3.9001 | 0.7188 | 1.2616 | -440.0739 | -416.4398 | 95.9739 | 101.8169 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.1.2+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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all_results.json
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"train_samples": 6750,
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"train_samples_per_second": 5.891,
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"train_steps_per_second": 0.045
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}
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config.json
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"architectures": [
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"GemmaForCausalLM"
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"model_type": "gemma",
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"num_hidden_layers": 28,
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"num_key_value_heads": 16,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"torch_dtype": "bfloat16",
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"use_cache": false,
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"vocab_size": 256000
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}
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generation_config.json
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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