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SmolLM-360M-Instruct-dpo-16k
dmariko/SmolLM-360M-Instruct-dpo-16k
SmolLM-360M-Instruct-dpo-16k is a machine learning model from dmariko. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- cc-by-nc-4.0
- Model type
- llama
- Access
- Public
- Created
- Sep 11, 2024
- Updated
- Sep 12, 2024
- SHA
- cf11bd8e
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. -->
SmolLM-360M-Instruct-dpo-16k
This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8873
- Rewards/chosen: 0.0047
- Rewards/rejected: 0.3539
- Rewards/accuracies: 0.0326
- Rewards/margins: -0.3493
- Logps/rejected: -470.7575
- Logps/chosen: -546.0133
- Logits/rejected: 0.3014
- Logits/chosen: 0.6045
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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5225 | 0.9999 | 3368 | 0.8679 | 0.0092 | 0.3258 | 0.0337 | -0.3166 | -471.0385 | -545.9679 | 0.3212 | 0.6250 |
| 0.4511 | 2.0 | 6737 | 0.8863 | 0.0171 | 0.3649 | 0.0283 | -0.3477 | -470.6477 | -545.8885 | 0.2889 | 0.5939 |
| 0.4453 | 2.9999 | 10105 | 0.8880 | 0.0006 | 0.3516 | 0.0304 | -0.3510 | -470.7807 | -546.0537 | 0.3259 | 0.6291 |
| 0.4439 | 4.0 | 13474 | 0.8894 | 0.0067 | 0.3598 | 0.0228 | -0.3531 | -470.6990 | -545.9932 | 0.2699 | 0.5815 |
| 0.4441 | 4.9999 | 16842 | 0.8881 | 0.0058 | 0.3569 | 0.0293 | -0.3511 | -470.7278 | -546.0020 | 0.2999 | 0.6028 |
| 0.4442 | 5.9991 | 20208 | 0.8873 | 0.0047 | 0.3539 | 0.0326 | -0.3493 | -470.7575 | -546.0133 | 0.3014 | 0.6045 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Type
- llama
- License
- cc-by-nc-4.0
- Languages
- en
- Created
- Sep 11, 2024
- Updated
- Sep 12, 2024