metadata
base_model: jetmoe/jetmoe-8b-sft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: jetmoe-8b-chat
results: []
jetmoe-8b-chat
This model is a fine-tuned version of jetmoe-8b-sft on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6372
- Rewards/chosen: -0.0901
- Rewards/rejected: -0.2250
- Rewards/accuracies: 0.7148
- Rewards/margins: 0.1349
- Logps/rejected: -289.3396
- Logps/chosen: -286.2378
- Logits/rejected: -2.9020
- Logits/chosen: -2.9443
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: 5e-07
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6664 | 0.42 | 200 | 0.6622 | -0.0185 | -0.0869 | 0.6997 | 0.0684 | -275.5274 | -279.0778 | -2.9127 | -2.9572 |
| 0.6428 | 0.84 | 400 | 0.6372 | -0.0901 | -0.2250 | 0.7148 | 0.1349 | -289.3396 | -286.2378 | -2.9020 | -2.9443 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2