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--- |
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license: apache-2.0 |
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base_model: studio-ousia/luke-japanese-base-lite |
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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: out |
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results: [] |
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--- |
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## Fine-tuning |
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- this model was trained to classify whether input text comes from "chosen sentence" or "rejected sentence" |
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- the probability (logits after passing softmax function) in last layer of this model can be used to quantify the preference from user input |
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- fine-tuned [studio-ousia/mluke-large-lite](https://huggingface.co/studio-ousia/mluke-large-lite) via full parameter tuning using [open-preference-v0.3](https://huggingface.co/datasets/ryota39/open_preference-v0.3) |
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- trained on bf16 format |
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- Label 0 stands for rejected sentence |
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- Label 1 stands for chosen sentence |
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- **Note that this model can handle only 512 tokens in maximum** |
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- **The limitation arises from Luke-based pre-trained model** |
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## Metric |
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- train and validation split |
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|train loss|eval loss|accuracy|recall|precision|f1-score| |
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|:---|:---|:---|:---|:---|:---| |
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|0.1427|0.2009|9282|0.9383|0.9198|0.9290| |
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- test split |
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|accuracy|recall|precision|f1-score| |
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|:---|:---|:---|:---| |
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|0.9310|0.9199|0.9408|0.9302| |
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- confusion matrix when test split |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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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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- 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 | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.316 | 1.0 | 1479 | 0.2245 | 0.9127 | 0.9027 | 0.9251 | 0.9138 | |
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| 0.1696 | 2.0 | 2958 | 0.1869 | 0.9308 | 0.9234 | 0.9395 | 0.9314 | |
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| 0.1427 | 3.0 | 4437 | 0.2009 | 0.9283 | 0.9198 | 0.9384 | 0.9290 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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