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--- |
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license: mit |
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base_model: facebook/xlm-v-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-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_delta |
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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: 0.3333333333333333 |
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- name: F1 |
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type: f1 |
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value: 0.16666666666666666 |
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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-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_delta |
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This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-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: 1.0987 |
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- Accuracy: 0.3333 |
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- F1: 0.1667 |
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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: 11213 |
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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: 500 |
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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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| 1.0872 | 1.09 | 500 | 1.0884 | 0.3978 | 0.3194 | |
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| 1.0993 | 2.17 | 1000 | 1.0988 | 0.3333 | 0.1667 | |
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| 1.0983 | 3.26 | 1500 | 1.1525 | 0.3329 | 0.1713 | |
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| 1.0994 | 4.35 | 2000 | 1.0997 | 0.3333 | 0.1667 | |
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| 1.0998 | 5.43 | 2500 | 1.0991 | 0.3333 | 0.1667 | |
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| 1.0997 | 6.52 | 3000 | 1.0987 | 0.3333 | 0.1667 | |
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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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