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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- pytorch
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- XLMRobertaForTokenClassification
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- named-entity-recognition
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- wikipedia
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- generated_from_trainer
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model-index:
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- name: xlm-roberta-base-wikineural
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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-base-wikineural
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0467
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 128
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- seed: 37912547
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 100000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:------:|:---------------:|
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| 0.0858 | 0.14 | 10000 | 0.0817 |
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| 0.0719 | 0.28 | 20000 | 0.0660 |
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| 0.0656 | 0.43 | 30000 | 0.0631 |
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| 0.0598 | 0.57 | 40000 | 0.0574 |
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| 0.0551 | 0.71 | 50000 | 0.0534 |
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| 0.0523 | 0.85 | 60000 | 0.0512 |
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| 0.0519 | 0.99 | 70000 | 0.0484 |
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| 0.0418 | 1.13 | 80000 | 0.0480 |
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| 0.042 | 1.28 | 90000 | 0.0469 |
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| 0.041 | 1.42 | 100000 | 0.0467 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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runs/Dec09_08-54-55_584b4064680c/events.out.tfevents.1702165372.584b4064680c.508.4
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version https://git-lfs.github.com/spec/v1
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oid sha256:4a1a7bac1e745b82d0e222c9040212d6476b9ae561e9d224b6b741d42a752841
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size 364
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