datagen_round_0
This model is a fine-tuned version of cognitivecomputations/dolphin-2.9.4-llama3.1-8b on the data/chunk0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5236
- Rewards/chosen: 0.1876
- Rewards/rejected: -4.2640
- Rewards/accuracies: 0.8400
- Rewards/margins: 4.4516
- Logps/rejected: -571.7687
- Logps/chosen: -81.3018
- Logits/rejected: -1.3050
- Logits/chosen: -1.2708
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: 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
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5544 | 0.2629 | 100 | 0.5820 | 0.0636 | -2.8538 | 0.7800 | 2.9174 | -430.7426 | -93.7035 | -1.3105 | -1.2969 |
| 0.5709 | 0.5258 | 200 | 0.5423 | 0.1260 | -3.5098 | 0.8200 | 3.6358 | -496.3472 | -87.4606 | -1.3295 | -1.2959 |
| 0.5502 | 0.7887 | 300 | 0.5249 | 0.2054 | -3.9454 | 0.8400 | 4.1508 | -539.9067 | -79.5220 | -1.3048 | -1.2761 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
meta-llama/Llama-3.1-8B