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NicholasCorrado_-_tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo-gguf
RichardErkhov/NicholasCorrado_-_tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo-gguf
NicholasCorrado_-_tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Mar 16, 2025
- Updated
- Mar 16, 2025
- SHA
- c318fe59
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo - GGUF
- Model creator: https://huggingface.co/NicholasCorrado/
- Original model: https://huggingface.co/NicholasCorrado/tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo/
Original model description:
library_name: transformers license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- alignment-handbook
- generated_from_trainer datasets:
- data/ui_math_ref
- data/ui_coding_ref model-index:
- name: tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo results: []
<!-- 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. -->
tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on the data/ui_math_ref and the data/ui_coding_ref datasets. It achieves the following results on the evaluation set:
- Loss: 0.4193
- Rewards/chosen: -0.6057
- Rewards/rejected: -1.6972
- Rewards/accuracies: 0.7188
- Rewards/margins: 1.0915
- Logps/rejected: -538.1440
- Logps/chosen: -448.5587
- Logits/rejected: -2.6494
- Logits/chosen: -2.6509
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- total_eval_batch_size: 128
- 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
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Created
- Mar 16, 2025
- Updated
- Mar 16, 2025