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--- |
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license: mit |
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base_model: microsoft/mdeberta-v3-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tweet_sentiment_multilingual |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all |
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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: tweet_sentiment_multilingual |
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type: tweet_sentiment_multilingual |
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config: all |
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split: validation |
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args: all |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6361882716049383 |
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- name: F1 |
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type: f1 |
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value: 0.6387023843949189 |
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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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# scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all |
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the tweet_sentiment_multilingual dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0269 |
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- Accuracy: 0.6362 |
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- F1: 0.6387 |
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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: 32 |
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- seed: 66 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.8991 | 1.09 | 500 | 0.8258 | 0.6265 | 0.6117 | |
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| 0.6873 | 2.17 | 1000 | 0.8627 | 0.6481 | 0.6502 | |
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| 0.5102 | 3.26 | 1500 | 0.9726 | 0.6516 | 0.6440 | |
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| 0.3825 | 4.35 | 2000 | 1.1881 | 0.6578 | 0.6540 | |
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| 0.2946 | 5.43 | 2500 | 1.2475 | 0.6532 | 0.6554 | |
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| 0.228 | 6.52 | 3000 | 1.5294 | 0.6435 | 0.6458 | |
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| 0.2006 | 7.61 | 3500 | 1.6058 | 0.6389 | 0.6342 | |
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| 0.159 | 8.7 | 4000 | 1.5956 | 0.6528 | 0.6510 | |
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| 0.1334 | 9.78 | 4500 | 1.8463 | 0.6478 | 0.6409 | |
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| 0.1052 | 10.87 | 5000 | 2.0269 | 0.6362 | 0.6387 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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