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--- |
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license: llama3 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-8B |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: llama3-8B_less_data_for_fact_update |
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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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# llama3-8B_less_data_for_fact_update |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7586 |
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- Accuracy: 0.7733 |
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- Precision: 0.8015 |
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- Recall: 0.7267 |
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- F1 score: 0.7622 |
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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: 8 |
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- eval_batch_size: 4 |
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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: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| 0.8492 | 0.5 | 200 | 0.8538 | 0.65 | 0.6923 | 0.54 | 0.6067 | |
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| 0.7574 | 1.0 | 400 | 0.6427 | 0.7267 | 0.8036 | 0.6 | 0.6870 | |
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| 0.5003 | 1.5 | 600 | 0.5917 | 0.73 | 0.7066 | 0.7867 | 0.7445 | |
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| 0.4629 | 2.0 | 800 | 0.6470 | 0.7567 | 0.8235 | 0.6533 | 0.7286 | |
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| 0.3114 | 2.5 | 1000 | 0.6980 | 0.6967 | 0.7438 | 0.6 | 0.6642 | |
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| 0.3031 | 3.0 | 1200 | 0.6128 | 0.7567 | 0.8130 | 0.6667 | 0.7326 | |
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| 0.1783 | 3.5 | 1400 | 0.7288 | 0.7667 | 0.8175 | 0.6867 | 0.7464 | |
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| 0.1737 | 4.0 | 1600 | 0.7242 | 0.7533 | 0.7969 | 0.68 | 0.7338 | |
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| 0.0924 | 4.5 | 1800 | 0.7214 | 0.7733 | 0.7808 | 0.76 | 0.7703 | |
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| 0.0669 | 5.0 | 2000 | 0.7586 | 0.7733 | 0.8015 | 0.7267 | 0.7622 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
