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Browse files- README.md +79 -0
- pytorch_model.bin +1 -1
README.md
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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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datasets:
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- emotion
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metrics:
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- f1
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model-index:
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- name: test01
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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: F1
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type: f1
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value: 0.9104824364647098
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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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# test01
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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 emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3902
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- F1: 0.9105
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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: 2e-05
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- train_batch_size: 64
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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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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 1.4186 | 1.0 | 250 | 1.1125 | 0.4765 |
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| 0.9485 | 2.0 | 500 | 0.7212 | 0.8291 |
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| 0.6309 | 3.0 | 750 | 0.5014 | 0.8881 |
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| 0.4772 | 4.0 | 1000 | 0.4186 | 0.9122 |
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| 0.4078 | 5.0 | 1250 | 0.3902 | 0.9105 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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pytorch_model.bin
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 133517617
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version https://git-lfs.github.com/spec/v1
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size 133517617
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