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---
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license: apache-2.0
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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: google-bert/bert-large-uncased
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datasets:
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- emotion
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metrics:
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- accuracy
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model-index:
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- name: emotion-bert-large-uncased-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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# emotion-bert-large-uncased-lora |
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This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1651 |
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- Accuracy: 0.9315 |
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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: 0.0005 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 250 | 0.4509 | 0.848 | |
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| 0.6387 | 2.0 | 500 | 0.2250 | 0.9225 | |
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| 0.6387 | 3.0 | 750 | 0.1771 | 0.9215 | |
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| 0.1705 | 4.0 | 1000 | 0.1651 | 0.9315 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
