79 lines
2.8 KiB
Markdown
79 lines
2.8 KiB
Markdown
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---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
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tags:
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- alignment-handbook
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- kto
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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model-index:
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- name: llama-3-8b-base-kto-ultrafeedback-8xh200
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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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# llama-3-8b-base-kto-ultrafeedback-8xh200
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3658
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- Rewards/chosen: 0.1622
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- Logps/chosen: -286.2337
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- Rewards/rejected: -2.5444
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- Logps/rejected: -292.3963
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- Rewards/margins: 2.7066
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- Kl: 0.0
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- Logits/chosen: -140467840.0
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- Logits/rejected: -139209600.0
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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: 4
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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: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Logps/chosen | Rewards/rejected | Logps/rejected | Rewards/margins | Kl | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---------------:|:---:|:-------------:|:---------------:|
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| 1.5841 | 0.2094 | 200 | 0.3971 | -0.1699 | -289.5548 | -1.7146 | -284.0978 | 1.5447 | 0.0 | -151004736.0 | -149476768.0 |
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| 1.404 | 0.4188 | 400 | 0.3773 | -0.0342 | -288.1983 | -2.3874 | -290.8255 | 2.3531 | 0.0 | -143785152.0 | -142386976.0 |
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| 1.4253 | 0.6283 | 600 | 0.3684 | -0.3211 | -291.0670 | -3.1407 | -298.3589 | 2.8196 | 0.0 | -145117536.0 | -143700400.0 |
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| 1.4432 | 0.8377 | 800 | 0.3658 | 0.1622 | -286.2337 | -2.5444 | -292.3963 | 2.7066 | 0.0 | -140467840.0 | -139209600.0 |
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### Framework versions
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- Transformers 4.51.0
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.21.4
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