Downloads · 30 days
8
24% of all-time downloads
dpo_mcqa_quantizedBitsAndBytes
chrisswillss98/dpo_mcqa_quantizedBitsAndBytes
dpo_mcqa_quantizedBitsAndBytes is a machine learning model from chrisswillss98. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
34
Public
Repo size
1.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors807 MB · 100%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jun 14, 2024
- Updated
- Jun 14, 2024
- SHA
- 7d56e288
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
mcqa_quant_BBQ
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9790
- Rewards/chosen: -0.9912
- Rewards/rejected: -0.9047
- Rewards/accuracies: 0.5
- Rewards/margins: -0.0865
- Logps/rejected: -26.9191
- Logps/chosen: -28.3753
- Logits/rejected: -3.3916
- Logits/chosen: -3.3931
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: 8
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6638 | 1.7241 | 50 | 0.7089 | -0.0201 | 0.0054 | 0.3462 | -0.0254 | -17.8186 | -18.6642 | -3.5325 | -3.5335 |
| 0.5696 | 3.4483 | 100 | 0.7434 | -0.2832 | -0.2559 | 0.4615 | -0.0273 | -20.4312 | -21.2954 | -3.4911 | -3.4921 |
| 0.3751 | 5.1724 | 150 | 0.8633 | -0.5219 | -0.4777 | 0.4615 | -0.0443 | -22.6490 | -23.6828 | -3.4444 | -3.4462 |
| 0.2126 | 6.8966 | 200 | 1.0177 | -0.7687 | -0.6209 | 0.3846 | -0.1478 | -24.0814 | -26.1501 | -3.4037 | -3.4053 |
| 0.1764 | 8.6207 | 250 | 0.9790 | -0.9912 | -0.9047 | 0.5 | -0.0865 | -26.9191 | -28.3753 | -3.3916 | -3.3931 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jun 14, 2024
- Updated
- Jun 14, 2024