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--- |
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base_model: meta-llama/Llama-2-7b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: qlora-adapter-Llama-2-7b-hf-databricks-dolly-15k |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# qlora-adapter-Llama-2-7b-hf-databricks-dolly-15k |
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This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1313 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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Trained on RTX A5000 - 24GB GPU. The training took 3 hours 31 mins on the datasets with 12008 train samples and 1501 validation samples |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.1584 | 0.08 | 1000 | 1.1782 | |
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| 1.0667 | 0.17 | 2000 | 1.1710 | |
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| 1.0662 | 0.25 | 3000 | 1.1599 | |
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| 1.0517 | 0.33 | 4000 | 1.1569 | |
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| 1.0479 | 0.42 | 5000 | 1.1502 | |
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| 1.0516 | 0.5 | 6000 | 1.1441 | |
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| 1.0612 | 0.58 | 7000 | 1.1397 | |
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| 1.0235 | 0.67 | 8000 | 1.1361 | |
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| 1.0259 | 0.75 | 9000 | 1.1339 | |
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| 1.0485 | 0.83 | 10000 | 1.1320 | |
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| 1.0406 | 0.92 | 11000 | 1.1314 | |
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| 1.0393 | 1.0 | 12000 | 1.1313 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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