End of training
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README.md
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---
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license: mit
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base_model: xlm-roberta-base
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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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model-index:
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- name: 16class_11k_newtest_xlm_roberta_base_25nov_v2_8epoch
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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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# 16class_11k_newtest_xlm_roberta_base_25nov_v2_8epoch
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1142
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- Accuracy: 0.9706
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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: 1e-05
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- train_batch_size: 16
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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: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.7244 | 1.0 | 826 | 0.6693 | 0.8036 |
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| 0.6119 | 2.0 | 1652 | 0.4189 | 0.8734 |
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| 0.5004 | 3.0 | 2478 | 0.3088 | 0.9141 |
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| 0.3626 | 4.0 | 3304 | 0.2287 | 0.9339 |
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| 0.2776 | 5.0 | 4130 | 0.1735 | 0.9513 |
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| 0.2445 | 6.0 | 4956 | 0.1446 | 0.9606 |
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| 0.1944 | 7.0 | 5782 | 0.1192 | 0.9682 |
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| 0.1633 | 8.0 | 6608 | 0.1142 | 0.9706 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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