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--- |
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base_model: gokuls/model_v1_complete_training_wt_init_48_small_freeze_new |
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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-emotion-logit_KD-small |
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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: 0.9335 |
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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-emotion-logit_KD-small |
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This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_small_freeze_new](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_small_freeze_new) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2473 |
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- Accuracy: 0.9335 |
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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: 50 |
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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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| 1.4023 | 1.0 | 250 | 0.5204 | 0.8825 | |
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| 0.3903 | 2.0 | 500 | 0.3014 | 0.91 | |
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| 0.2438 | 3.0 | 750 | 0.2849 | 0.9185 | |
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| 0.1778 | 4.0 | 1000 | 0.2489 | 0.9265 | |
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| 0.1394 | 5.0 | 1250 | 0.2878 | 0.9205 | |
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| 0.1218 | 6.0 | 1500 | 0.2887 | 0.923 | |
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| 0.1083 | 7.0 | 1750 | 0.2788 | 0.9285 | |
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| 0.1019 | 8.0 | 2000 | 0.2373 | 0.928 | |
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| 0.0898 | 9.0 | 2250 | 0.2473 | 0.9335 | |
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| 0.0817 | 10.0 | 2500 | 0.2822 | 0.926 | |
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| 0.0827 | 11.0 | 2750 | 0.2474 | 0.926 | |
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| 0.0733 | 12.0 | 3000 | 0.2329 | 0.9285 | |
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| 0.0631 | 13.0 | 3250 | 0.2301 | 0.929 | |
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| 0.06 | 14.0 | 3500 | 0.2565 | 0.9295 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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