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--- |
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license: apache-2.0 |
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base_model: studio-ousia/mluke-large-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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<!-- 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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## 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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|0.114|0.1615|0.9399|0.9459|0.9346|0.9402| |
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- test split |
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|accuracy|recall|precision|f1-score| |
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|:---|:---|:---|:---| |
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|0.9416|0.9319|0.9504|0.9411| |
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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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| 0.4109 | 1.0 | 1479 | 0.2462 | 0.9003 | 0.8710 | 0.9399 | 0.9041 | |
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| 0.1579 | 2.0 | 2958 | 0.1573 | 0.9399 | 0.9495 | 0.9293 | 0.9393 | |
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| 0.114 | 3.0 | 4437 | 0.1615 | 0.9399 | 0.9346 | 0.9460 | 0.9403 | |
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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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