End of training
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README.md
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---
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
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tags:
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- generated_from_trainer
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model-index:
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- name: XlM-roberta-AS-HU-f1-score
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results: []
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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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# XlM-roberta-AS-HU-f1-score
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1081
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- F1-score: 0.8389
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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: 16
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- eval_batch_size: 8
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1-score |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.6852 | 1.0 | 64 | 0.6780 | 0.3697 |
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| 0.6514 | 2.0 | 128 | 0.5578 | 0.6958 |
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| 0.5075 | 3.0 | 192 | 0.5620 | 0.7619 |
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| 0.401 | 4.0 | 256 | 0.5068 | 0.7688 |
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| 0.2288 | 5.0 | 320 | 0.6490 | 0.8084 |
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| 0.1424 | 6.0 | 384 | 0.7662 | 0.8350 |
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| 0.0837 | 7.0 | 448 | 0.9138 | 0.8389 |
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| 0.0463 | 8.0 | 512 | 1.0355 | 0.8247 |
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| 0.0108 | 9.0 | 576 | 1.0874 | 0.8345 |
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| 0.0069 | 10.0 | 640 | 1.1081 | 0.8389 |
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### Framework versions
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- Transformers 4.41.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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runs/Jun01_17-57-47_raul-MS-7B98/events.out.tfevents.1717282672.raul-MS-7B98.5810.0
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