End of training
Browse files- README.md +82 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model: bert-base-multilingual-cased
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tags:
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- generated_from_trainer
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datasets:
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- glue
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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: bert-base-multilingual-cased-finetuned
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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: glue
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type: glue
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config: mrpc
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split: validation
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args: mrpc
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8014705882352942
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- name: F1
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type: f1
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value: 0.863406408094435
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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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# bert-base-multilingual-cased-finetuned
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5381
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- Accuracy: 0.8015
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- F1: 0.8634
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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: 8
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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: 3.0
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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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| No log | 1.0 | 459 | 0.5459 | 0.7696 | 0.8469 |
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| 0.6057 | 2.0 | 918 | 0.6090 | 0.7230 | 0.8306 |
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| 0.5287 | 3.0 | 1377 | 0.5381 | 0.8015 | 0.8634 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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-
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size 711488305
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version https://git-lfs.github.com/spec/v1
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size 711488305
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