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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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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: jq_emo_gpt |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: emotion |
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type: emotion |
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config: split |
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split: validation |
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args: split |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.941 |
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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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# jq_emo_gpt |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3379 |
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- Accuracy: 0.941 |
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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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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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- lr_scheduler_warmup_steps: 16000 |
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- num_epochs: 10 |
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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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| 0.7328 | 1.0 | 16000 | 0.6227 | 0.899 | |
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| 0.3989 | 2.0 | 32000 | 0.4351 | 0.927 | |
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| 0.2888 | 3.0 | 48000 | 0.3162 | 0.9385 | |
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| 0.2325 | 4.0 | 64000 | 0.2936 | 0.9445 | |
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| 0.2774 | 5.0 | 80000 | 0.2903 | 0.94 | |
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| 0.1423 | 6.0 | 96000 | 0.3410 | 0.9405 | |
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| 0.1681 | 7.0 | 112000 | 0.3259 | 0.9385 | |
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| 0.1743 | 8.0 | 128000 | 0.3225 | 0.9415 | |
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| 0.1011 | 9.0 | 144000 | 0.3356 | 0.942 | |
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| 0.1138 | 10.0 | 160000 | 0.3379 | 0.941 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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