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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 +7 -16
  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: 0.6948
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  ## Model description
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@@ -36,31 +36,22 @@ More information needed
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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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  - 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: 15
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  ### Training results
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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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  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: 0.5121
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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: 5e-06
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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: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.5016 | 1.1 | 500 | 0.4122 |
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+ | 0.3374 | 2.2 | 1000 | 0.5111 |
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+ | 0.302 | 3.3 | 1500 | 0.5090 |
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+ | 0.2496 | 4.4 | 2000 | 0.5121 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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