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--- |
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library_name: peft |
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license: other |
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base_model: ibm-granite/granite-3.3-8b-instruct |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: factory_granite_results |
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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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# factory_granite_results |
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This model is a fine-tuned version of [ibm-granite/granite-3.3-8b-instruct](https://huggingface.co/ibm-granite/granite-3.3-8b-instruct) on the train dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2523 |
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- Accuracy: 0.9475 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 8 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 9.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.4051 | 1.0 | 32 | 0.4305 | 0.8978 | |
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| 0.2886 | 2.0 | 64 | 0.3232 | 0.9206 | |
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| 0.2289 | 3.0 | 96 | 0.2742 | 0.9323 | |
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| 0.1925 | 4.0 | 128 | 0.2514 | 0.9387 | |
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| 0.1079 | 5.0 | 160 | 0.2456 | 0.9420 | |
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| 0.0968 | 6.0 | 192 | 0.2410 | 0.9454 | |
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| 0.0835 | 7.0 | 224 | 0.2464 | 0.9466 | |
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| 0.0716 | 8.0 | 256 | 0.2516 | 0.9472 | |
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| 0.0611 | 9.0 | 288 | 0.2523 | 0.9475 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.52.4 |
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- Pytorch 2.7.0 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
