Small LLMs
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Collection of Fine Tuned Small LLMs
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13 items
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Note: This model card has been generated automatically according to the information the Trainer had access to. Visit the model card to see the full description.
zephyr-danube-sft-qlora
This model is a fine-tuned version of h2oai/h2o-danube-1.8b-base on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
- Loss: 1.0893
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 128
- total_train_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
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0883 | 0.9998 | 1140 | 1.0893 |
Framework versions
- PEFT 0.7.1
- Transformers 4.40.1
- Pytorch 2.1.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for Ritvik19/zephyr-danube-sft-qlora
Base model
h2oai/h2o-danube-1.8b-base