Asynchronous RLHF
Collection
Models and datasets for asynchronous rlhf paper, see code at https://github.com/mnoukhov/async_rlhf
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10 items
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Updated
pythia2.8b-rm-tldr6.9b
This model is a fine-tuned version of mnoukhov/pythia2.8b-sft-tldr on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3979
- Accuracy: 0.8129
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5048 | 0.2006 | 291 | 0.4736 | 0.7684 |
| 0.4188 | 0.4011 | 582 | 0.4287 | 0.7951 |
| 0.3628 | 0.6017 | 873 | 0.4141 | 0.8028 |
| 0.3203 | 0.8022 | 1164 | 0.3979 | 0.8129 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for mnoukhov/pythia2.8b-rm-tldr6.9b
Base model
EleutherAI/pythia-2.8b-deduped
Finetuned
mnoukhov/pythia2.8b-sft-tldr