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--- |
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license: llama2 |
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base_model: h2oai/h2ogpt-16k-codellama-7b-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: h2ogpt-16k-codellama-7b-instruct-finetuned-1-2024-03-06-16 |
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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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# h2ogpt-16k-codellama-7b-instruct-finetuned-1-2024-03-06-16 |
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This model is a fine-tuned version of [h2oai/h2ogpt-16k-codellama-7b-instruct](https://huggingface.co/h2oai/h2ogpt-16k-codellama-7b-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0141 |
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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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## 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: 0.0003 |
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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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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.6967 | 1.17 | 20 | 0.4241 | |
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| 0.2982 | 2.33 | 40 | 0.2148 | |
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| 0.1461 | 3.5 | 60 | 0.1113 | |
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| 0.0856 | 4.66 | 80 | 0.0586 | |
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| 0.0631 | 5.83 | 100 | 0.0419 | |
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| 0.0577 | 6.99 | 120 | 0.0318 | |
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| 0.064 | 8.16 | 140 | 0.0464 | |
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| 0.0444 | 9.33 | 160 | 0.0308 | |
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| 0.0463 | 10.49 | 180 | 0.0284 | |
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| 0.0372 | 11.66 | 200 | 0.0276 | |
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| 0.0345 | 12.82 | 220 | 0.0253 | |
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| 0.0384 | 13.99 | 240 | 0.0230 | |
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| 0.0313 | 15.15 | 260 | 0.0201 | |
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| 0.0246 | 16.32 | 280 | 0.0168 | |
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| 0.0196 | 17.49 | 300 | 0.0141 | |
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| 0.0166 | 18.65 | 320 | 0.0140 | |
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| 0.0146 | 19.82 | 340 | 0.0141 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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