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--- |
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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: my_awesome_model |
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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: test |
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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: 0.774 |
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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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# my_awesome_model |
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This model is a fine-tuned version of [](https://huggingface.co/) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6804 |
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- Accuracy: 0.774 |
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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: 5e-05 |
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- train_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 500 |
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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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| 1.6145 | 1.0 | 500 | 1.5603 | 0.3475 | |
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| 1.4622 | 2.0 | 1000 | 1.3149 | 0.4 | |
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| 1.2777 | 3.0 | 1500 | 1.2142 | 0.4365 | |
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| 1.1218 | 4.0 | 2000 | 1.0095 | 0.5915 | |
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| 0.8886 | 5.0 | 2500 | 0.8772 | 0.695 | |
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| 0.7649 | 6.0 | 3000 | 0.7803 | 0.7355 | |
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| 0.6818 | 7.0 | 3500 | 0.7220 | 0.7615 | |
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| 0.6268 | 8.0 | 4000 | 0.6870 | 0.773 | |
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| 0.5922 | 9.0 | 4500 | 0.6859 | 0.771 | |
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| 0.5658 | 10.0 | 5000 | 0.6804 | 0.774 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.14.1 |
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