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--- |
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license: llama2 |
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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/Llama-2-13b-hf |
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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: Llama2_13B_Task2_semantic_pred |
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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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# Llama2_13B_Task2_semantic_pred |
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This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3818 |
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- Accuracy: 0.9087 |
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- Precision: 0.9087 |
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- Recall: 0.9087 |
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- F1 score: 0.9087 |
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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: 8 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 score | Precision | Recall | Validation Loss | |
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|:-------------:|:------:|:----:|:--------:|:--------:|:---------:|:------:|:---------------:| |
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| 0.4564 | 0.2604 | 200 | 0.8214 | 0.8198 | 0.8311 | 0.8214 | 0.4378 | |
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| 0.3824 | 0.5208 | 400 | 0.8279 | 0.8279 | 0.8279 | 0.8279 | 0.4660 | |
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| 0.3609 | 0.7812 | 600 | 0.8631 | 0.8630 | 0.8635 | 0.8631 | 0.3303 | |
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| 0.3065 | 1.0417 | 800 | 0.8696 | 0.8695 | 0.8724 | 0.8696 | 0.3470 | |
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| 0.1987 | 1.3021 | 1000 | 0.8722 | 0.8722 | 0.8733 | 0.8722 | 0.3563 | |
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| 0.2043 | 1.5625 | 1200 | 0.9022 | 0.9020 | 0.9051 | 0.9022 | 0.3349 | |
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| 0.2193 | 1.8229 | 1400 | 0.8996 | 0.8996 | 0.8997 | 0.8996 | 0.3166 | |
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| 0.1674 | 2.0833 | 1600 | 0.8931 | 0.8930 | 0.8937 | 0.8931 | 0.3300 | |
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| 0.1226 | 2.3438 | 1800 | 0.3672 | 0.9087 | 0.9094 | 0.9087 | 0.9087 | |
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| 0.123 | 2.6042 | 2000 | 0.3862 | 0.9074 | 0.9091 | 0.9074 | 0.9073 | |
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| 0.0792 | 2.8646 | 2200 | 0.3818 | 0.9087 | 0.9087 | 0.9087 | 0.9087 | |
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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 |
