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aligner-v1-llama3-01
Ksgk-fy/aligner-v1-llama3-01
aligner-v1-llama3-01 is a machine learning model from Ksgk-fy. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- Apr 30, 2024
- Updated
- Apr 30, 2024
- SHA
- d300da49
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
aligner-v1-llama3-01
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4361
- Rewards/chosen: -0.0331
- Rewards/rejected: -0.0349
- Rewards/accuracies: 0.8333
- Rewards/margins: 0.0018
- Logps/rejected: -0.3493
- Logps/chosen: -0.3313
- Logits/rejected: -1.5592
- Logits/chosen: -1.5485
- Nll Loss: 1.3699
- Log Odds Ratio: -0.6618
- Log Odds Chosen: 0.0646
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: 8e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.8628 | 0.2105 | 15 | 2.7068 | -0.1219 | -0.1183 | 0.0 | -0.0036 | -1.1830 | -1.2191 | -1.8565 | -1.8340 | 2.6349 | -0.7190 | -0.0509 |
| 2.1044 | 0.4211 | 30 | 2.0553 | -0.0702 | -0.0687 | 0.1667 | -0.0015 | -0.6871 | -0.7024 | -1.6352 | -1.6218 | 1.9845 | -0.7082 | -0.0296 |
| 1.6915 | 0.6316 | 45 | 1.6323 | -0.0431 | -0.0436 | 0.8333 | 0.0006 | -0.4364 | -0.4305 | -1.6833 | -1.6715 | 1.5639 | -0.6842 | 0.0185 |
| 1.4279 | 0.8421 | 60 | 1.4361 | -0.0331 | -0.0349 | 0.8333 | 0.0018 | -0.3493 | -0.3313 | -1.5592 | -1.5485 | 1.3699 | -0.6618 | 0.0646 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Library
- peft
- License
- other
- Created
- Apr 30, 2024
- Updated
- Apr 30, 2024