juanako-7b-v2-UNA-v3
This model is a fine-tuned version of Intel/neural-chat-7b-v3-1 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.4658
- Rewards/chosen: -0.6178
- Rewards/rejected: -1.7640
- Rewards/accuracies: 0.7622
- Rewards/margins: 1.1462
- Logps/rejected: -239.1435
- Logps/chosen: -227.6597
- Logits/rejected: -2.2452
- Logits/chosen: -2.4812
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 14
- gradient_accumulation_steps: 16
- total_train_batch_size: 224
- total_eval_batch_size: 14
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4855 | 0.25 | 69 | 0.4897 | -0.7296 | -1.8563 | 0.7413 | 1.1266 | -240.0657 | -228.7776 | -2.2474 | -2.4843 |
| 0.4835 | 0.5 | 138 | 0.4734 | -0.5055 | -1.5652 | 0.7483 | 1.0597 | -237.1553 | -226.5366 | -2.2448 | -2.4811 |
| 0.5193 | 0.75 | 207 | 0.4717 | -0.6888 | -1.7561 | 0.7343 | 1.0673 | -239.0642 | -228.3696 | -2.2426 | -2.4783 |
| 0.4514 | 1.0 | 276 | 0.4658 | -0.6178 | -1.7640 | 0.7622 | 1.1462 | -239.1435 | -227.6597 | -2.2452 | -2.4812 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- Downloads last month
- 0
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.