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--- |
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base_model: daveni/twitter-xlm-roberta-emotion-es |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: base |
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results: [] |
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pipeline_tag: text-classification |
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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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# base |
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This model is a fine-tuned version of [daveni/twitter-xlm-roberta-emotion-es](https://huggingface.co./daveni/twitter-xlm-roberta-emotion-es) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4881 |
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- Accuracy: 0.8504 |
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- F1: 0.8119 |
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- Precision: 0.8454 |
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- Recall: 0.7810 |
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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: 16 |
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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 | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.667 | 1.0 | 32 | 0.5528 | 0.7283 | 0.6057 | 0.7571 | 0.5048 | |
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| 0.5241 | 2.0 | 64 | 0.4843 | 0.7874 | 0.7065 | 0.8228 | 0.6190 | |
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| 0.3046 | 3.0 | 96 | 0.4785 | 0.8031 | 0.7423 | 0.8090 | 0.6857 | |
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| 0.1631 | 4.0 | 128 | 0.4776 | 0.8228 | 0.7644 | 0.8488 | 0.6952 | |
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| 0.097 | 5.0 | 160 | 0.4881 | 0.8504 | 0.8119 | 0.8454 | 0.7810 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
