gpt-neo-125m_hh_reward
This model is a fine-tuned version of EleutherAI/gpt-neo-125m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7503
- Rewards/chosen: -4.2523
- Rewards/rejected: -4.3731
- Rewards/accuracies: 0.5625
- Rewards/margins: 0.1208
- Logps/rejected: -168.5040
- Logps/chosen: -147.3926
- Logits/rejected: -11.6528
- Logits/chosen: -11.5062
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- training_steps: 4050
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.8022 | 0.2 | 2000 | 0.7737 | -4.8718 | -5.0523 | 0.5724 | 0.1805 | -175.2956 | -153.5872 | -11.7730 | -11.6673 |
| 0.7336 | 0.4 | 4000 | 0.7503 | -4.2523 | -4.3731 | 0.5625 | 0.1208 | -168.5040 | -147.3926 | -11.6528 | -11.5062 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for amirabdullah19852020/gpt-neo-125m_hh_reward
Base model
EleutherAI/gpt-neo-125m