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--- |
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base_model: gokuls/model_v1_complete_training_wt_init_48_mini |
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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: hbertv1-mini-wt-48-emotion |
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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: 0.908 |
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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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# hbertv1-mini-wt-48-emotion |
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This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_mini](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_mini) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2561 |
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- Accuracy: 0.908 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 33 |
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- distributed_type: multi-GPU |
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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: 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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| 1.0852 | 1.0 | 250 | 0.5567 | 0.8195 | |
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| 0.4522 | 2.0 | 500 | 0.3409 | 0.8775 | |
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| 0.3152 | 3.0 | 750 | 0.3007 | 0.8885 | |
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| 0.2646 | 4.0 | 1000 | 0.2999 | 0.9045 | |
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| 0.23 | 5.0 | 1250 | 0.2842 | 0.8945 | |
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| 0.205 | 6.0 | 1500 | 0.2658 | 0.9035 | |
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| 0.1871 | 7.0 | 1750 | 0.2674 | 0.902 | |
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| 0.1623 | 8.0 | 2000 | 0.2561 | 0.908 | |
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| 0.1488 | 9.0 | 2250 | 0.2529 | 0.9075 | |
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| 0.1379 | 10.0 | 2500 | 0.2523 | 0.908 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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