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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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- f1
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model-index:
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- name: llama-1b-sst-2
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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-sst-2
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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: 0.3046
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- Accuracy: 0.8761
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- F1: 0.8805
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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 | F1 |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
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| No log | 0.1900 | 100 | 0.6003 | 0.6858 | 0.7375 |
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| No log | 0.3800 | 200 | 0.4186 | 0.8154 | 0.8282 |
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| No log | 0.5701 | 300 | 0.3709 | 0.8463 | 0.8511 |
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| No log | 0.7601 | 400 | 0.3565 | 0.8532 | 0.8612 |
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| 2.0823 | 0.9501 | 500 | 0.3391 | 0.8589 | 0.8591 |
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| 2.0823 | 1.1387 | 600 | 0.3303 | 0.8681 | 0.8686 |
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| 2.0823 | 1.3287 | 700 | 0.3285 | 0.8704 | 0.8660 |
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| 2.0823 | 1.5188 | 800 | 0.3177 | 0.8681 | 0.8715 |
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| 2.0823 | 1.7088 | 900 | 0.3406 | 0.8567 | 0.8691 |
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| 1.3266 | 1.8988 | 1000 | 0.3094 | 0.8842 | 0.8843 |
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| 1.3266 | 2.0874 | 1100 | 0.3051 | 0.8819 | 0.8841 |
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| 1.3266 | 2.2774 | 1200 | 0.3046 | 0.8784 | 0.8817 |
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| 1.3266 | 2.4675 | 1300 | 0.3041 | 0.8773 | 0.8810 |
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| 1.3266 | 2.6575 | 1400 | 0.3034 | 0.8773 | 0.8810 |
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| 1.2318 | 2.8475 | 1500 | 0.3046 | 0.8761 | 0.8805 |
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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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