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README.md
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---
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library_name: peft
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license: llama3.2
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base_model: meta-llama/Llama-3.2-1B-Instruct
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: llama-1b-yelp-5
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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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# llama-1b-yelp-5
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This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2241
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- Accuracy: 0.4791
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- Precision: 0.4724
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- Recall: 0.4769
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- F1: 0.4736
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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: 0.0002
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: linear
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| No log | 0.2559 | 100 | 1.6861 | 0.3415 | 0.3301 | 0.3398 | 0.3321 |
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| No log | 0.5118 | 200 | 1.4513 | 0.3999 | 0.4029 | 0.3957 | 0.3946 |
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| No log | 0.7678 | 300 | 1.3685 | 0.4308 | 0.4189 | 0.4296 | 0.4209 |
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| No log | 1.0230 | 400 | 1.3152 | 0.4474 | 0.4399 | 0.4453 | 0.4403 |
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| 6.034 | 1.2790 | 500 | 1.2959 | 0.4547 | 0.4483 | 0.4532 | 0.4471 |
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| 6.034 | 1.5349 | 600 | 1.2663 | 0.4616 | 0.4559 | 0.4593 | 0.4566 |
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| 6.034 | 1.7908 | 700 | 1.2542 | 0.4674 | 0.4630 | 0.4647 | 0.4626 |
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| 6.034 | 2.0461 | 800 | 1.2405 | 0.4729 | 0.4673 | 0.4712 | 0.4684 |
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| 6.034 | 2.3020 | 900 | 1.2371 | 0.4783 | 0.4763 | 0.4777 | 0.4753 |
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| 4.7846 | 2.5579 | 1000 | 1.2266 | 0.4814 | 0.4741 | 0.4803 | 0.4762 |
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| 4.7846 | 2.8138 | 1100 | 1.2241 | 0.4791 | 0.4724 | 0.4769 | 0.4736 |
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.47.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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