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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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: CuATR-distilbert-LoRA |
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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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# CuATR-distilbert-LoRA |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6945 |
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- Accuracy: 0.5652 |
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- F1: 0.7222 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 14 |
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- mixed_precision_training: Native AMP |
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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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| 0.7007 | 0.67 | 1 | 0.6957 | 0.5652 | 0.7222 | |
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| 0.6984 | 2.0 | 3 | 0.6954 | 0.5652 | 0.7222 | |
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| 0.7075 | 2.67 | 4 | 0.6952 | 0.5652 | 0.7222 | |
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| 0.7 | 4.0 | 6 | 0.6951 | 0.5652 | 0.7222 | |
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| 0.6962 | 4.67 | 7 | 0.6950 | 0.5652 | 0.7222 | |
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| 0.7003 | 6.0 | 9 | 0.6948 | 0.5652 | 0.7222 | |
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| 0.6952 | 6.67 | 10 | 0.6947 | 0.5652 | 0.7222 | |
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| 0.7027 | 8.0 | 12 | 0.6946 | 0.5652 | 0.7222 | |
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| 0.6995 | 8.67 | 13 | 0.6946 | 0.5652 | 0.7222 | |
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| 0.6919 | 9.33 | 14 | 0.6945 | 0.5652 | 0.7222 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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