Training is completed!!!
Browse files
README.md
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---
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library_name: transformers
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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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- f1
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model-index:
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- name: model_large_batch
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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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# model_large_batch
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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: 0.7476
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- Accuracy: 0.7097
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- F1: 0.7082
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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: 32
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- eval_batch_size: 32
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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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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.7514 | 1.0 | 500 | 0.7058 | 0.6933 | 0.6904 |
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| 0.67 | 2.0 | 1000 | 0.6883 | 0.7063 | 0.7038 |
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| 0.602 | 3.0 | 1500 | 0.6912 | 0.7137 | 0.7136 |
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| 0.5294 | 4.0 | 2000 | 0.7174 | 0.7055 | 0.7036 |
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| 0.4834 | 5.0 | 2500 | 0.7476 | 0.7097 | 0.7082 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.5.0+cu121
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- Datasets 3.0.2
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- Tokenizers 0.19.1
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runs/Oct27_12-36-32_bbd658741b81/events.out.tfevents.1730032600.bbd658741b81.432.6
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f4814c2d3b535cb5e960b7ea71054a20e52fcc650ffb76ac25a0ccce7c6c759
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size 9453
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