Dan Semin
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update model card README.md
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README.md
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---
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license: mit
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tags:
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- text-classification
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- generated_from_trainer
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datasets:
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- xnli
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metrics:
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- accuracy
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model-index:
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- name: xnli_xlm_r_only_en
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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: xnli
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type: xnli
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config: en
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split: train
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args: en
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8506024096385543
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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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# xnli_xlm_r_only_en
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xnli dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5994
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- Accuracy: 0.8506
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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: 2e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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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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- lr_scheduler_warmup_steps: 100
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- num_epochs: 10
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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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| 0.5771 | 1.0 | 3068 | 0.4557 | 0.8229 |
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| 0.4272 | 2.0 | 6136 | 0.4174 | 0.8305 |
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| 0.3599 | 3.0 | 9204 | 0.4471 | 0.8353 |
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| 0.3064 | 4.0 | 12272 | 0.4394 | 0.8446 |
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| 0.2604 | 5.0 | 15340 | 0.4544 | 0.8482 |
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| 0.2226 | 6.0 | 18408 | 0.5036 | 0.8494 |
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| 0.1907 | 7.0 | 21476 | 0.5139 | 0.8522 |
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| 0.1654 | 8.0 | 24544 | 0.5454 | 0.8486 |
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| 0.1441 | 9.0 | 27612 | 0.5828 | 0.8498 |
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| 0.1304 | 10.0 | 30680 | 0.5994 | 0.8506 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.13.0
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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