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minilm-finetuned-emotion-class-model

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  2. model.safetensors +1 -1
  3. runs/Mar22_16-00-35_f092ea680da5/events.out.tfevents.1711123348.f092ea680da5.7301.0 +2 -2
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/MiniLM-L12-H384-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: minilm-finetuned-emotion-class-model
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+ results: []
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+ ---
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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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+
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+ # minilm-finetuned-emotion-class-model
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+
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+ This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1026
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+ - F1 Score: 0.6649
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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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: 20
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.8502 | 1.0 | 270 | 1.4798 | 0.5071 |
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+ | 1.3541 | 2.0 | 540 | 1.2377 | 0.5836 |
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+ | 1.1809 | 3.0 | 810 | 1.1675 | 0.6202 |
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+ | 1.0891 | 4.0 | 1080 | 1.1081 | 0.6522 |
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+ | 1.0205 | 5.0 | 1350 | 1.0815 | 0.6603 |
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+ | 0.9624 | 6.0 | 1620 | 1.0640 | 0.6645 |
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+ | 0.9185 | 7.0 | 1890 | 1.0572 | 0.6689 |
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+ | 0.8811 | 8.0 | 2160 | 1.0433 | 0.6693 |
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+ | 0.8531 | 9.0 | 2430 | 1.0479 | 0.6746 |
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+ | 0.8208 | 10.0 | 2700 | 1.0536 | 0.6697 |
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+ | 0.8014 | 11.0 | 2970 | 1.0564 | 0.6713 |
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+ | 0.7798 | 12.0 | 3240 | 1.0634 | 0.6716 |
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+ | 0.7568 | 13.0 | 3510 | 1.0744 | 0.6698 |
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+ | 0.7414 | 14.0 | 3780 | 1.0782 | 0.6704 |
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+ | 0.7265 | 15.0 | 4050 | 1.0810 | 0.6694 |
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+ | 0.7128 | 16.0 | 4320 | 1.0885 | 0.6684 |
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+ | 0.7054 | 17.0 | 4590 | 1.0917 | 0.6631 |
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+ | 0.6927 | 18.0 | 4860 | 1.0961 | 0.6678 |
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+ | 0.6848 | 19.0 | 5130 | 1.1005 | 0.6644 |
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+ | 0.6742 | 20.0 | 5400 | 1.1026 | 0.6649 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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