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scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base

Text Classification
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PyTorch
xlm-roberta
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +15 -14
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the indolem_sentiment dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6193
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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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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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 0.22 | 100 | 0.6056 |
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- | No log | 0.44 | 200 | 0.6052 |
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- | No log | 0.66 | 300 | 0.6101 |
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- | No log | 0.88 | 400 | 0.6056 |
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- | 0.6407 | 1.1 | 500 | 0.6091 |
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- | 0.6407 | 1.32 | 600 | 0.6126 |
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- | 0.6407 | 1.54 | 700 | 0.6084 |
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- | 0.6407 | 1.76 | 800 | 0.6293 |
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- | 0.6407 | 1.98 | 900 | 0.6134 |
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- | 0.6139 | 2.2 | 1000 | 0.6211 |
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- | 0.6139 | 2.42 | 1100 | 0.6450 |
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- | 0.6139 | 2.64 | 1200 | 0.6193 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the indolem_sentiment dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6948
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  ## Model description
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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: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.22 | 100 | 0.4912 |
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+ | No log | 0.44 | 200 | 0.4478 |
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+ | No log | 0.66 | 300 | 0.3455 |
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+ | No log | 0.88 | 400 | 0.5863 |
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+ | 0.4809 | 1.1 | 500 | 0.3823 |
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+ | 0.4809 | 1.32 | 600 | 0.5047 |
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+ | 0.4809 | 1.54 | 700 | 0.6501 |
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+ | 0.4809 | 1.76 | 800 | 0.3950 |
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+ | 0.4809 | 1.98 | 900 | 0.6762 |
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+ | 0.3425 | 2.2 | 1000 | 0.4929 |
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+ | 0.3425 | 2.42 | 1100 | 0.4172 |
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+ | 0.3425 | 2.64 | 1200 | 0.6390 |
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+ | 0.3425 | 2.86 | 1300 | 0.6948 |
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  ### Framework versions
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