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ft-smollm-135M-instruct-on-hf-ultrafeedback_rob
micost/ft-smollm-135M-instruct-on-hf-ultrafeedback_rob
ft-smollm-135M-instruct-on-hf-ultrafeedback_rob is a machine learning model from micost. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- llama
- Access
- Public
- Created
- Oct 22, 2024
- Updated
- Oct 22, 2024
- SHA
- 87a68cdb
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. -->
ft-smollm-135M-instruct-on-hf-ultrafeedback_rob
This model is a fine-tuned version of HuggingFaceTB/SmolLM-135M-Instruct on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 1.1429
- Rewards/chosen: -0.1303
- Rewards/rejected: -0.1304
- Rewards/accuracies: 0.4670
- Rewards/margins: 0.0000
- Logps/rejected: -1.3036
- Logps/chosen: -1.3032
- Logits/rejected: 27.7664
- Logits/chosen: 27.4331
- Nll Loss: 1.0675
- Log Odds Ratio: -0.7542
- Log Odds Chosen: 0.0132
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.3569 | 0.8 | 100 | 1.1429 | -0.1303 | -0.1304 | 0.4670 | 0.0000 | -1.3036 | -1.3032 | 27.7664 | 27.4331 | 1.0675 | -0.7542 | 0.0132 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Type
- llama
- License
- apache-2.0
- Created
- Oct 22, 2024
- Updated
- Oct 22, 2024