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ThuyNT03
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xlm-roberta-base-Final_VietNam-train-1

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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ThuyNT03 commited on
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Training completed!

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Files changed (4) hide show
  1. README.md +14 -14
  2. config.json +1 -1
  3. pytorch_model.bin +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ 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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7619
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- - Accuracy: 0.7
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- - F1: 0.7024
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  ## Model description
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@@ -42,7 +42,7 @@ The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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: 8
@@ -51,19 +51,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.0977 | 1.0 | 44 | 1.0718 | 0.45 | 0.3722 |
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- | 1.0671 | 2.0 | 88 | 0.9927 | 0.59 | 0.4903 |
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- | 0.9142 | 3.0 | 132 | 0.8291 | 0.63 | 0.5657 |
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- | 0.7471 | 4.0 | 176 | 0.7205 | 0.7 | 0.6894 |
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- | 0.6121 | 5.0 | 220 | 0.7444 | 0.71 | 0.7050 |
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- | 0.5646 | 6.0 | 264 | 0.7418 | 0.68 | 0.6853 |
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- | 0.4723 | 7.0 | 308 | 0.7566 | 0.7 | 0.7026 |
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- | 0.4328 | 8.0 | 352 | 0.7619 | 0.7 | 0.7024 |
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  ### Framework versions
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- - Transformers 4.32.1
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  - Pytorch 2.0.1+cu118
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- - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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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: 0.7562
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+ - Accuracy: 0.69
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+ - F1: 0.6976
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  ## Model description
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  - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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+ - seed: 41
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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: 8
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.0985 | 1.0 | 44 | 1.0870 | 0.41 | 0.2928 |
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+ | 0.9394 | 2.0 | 88 | 0.8415 | 0.66 | 0.6161 |
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+ | 0.7884 | 3.0 | 132 | 0.8431 | 0.65 | 0.5722 |
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+ | 0.6681 | 4.0 | 176 | 0.7143 | 0.68 | 0.6702 |
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+ | 0.5849 | 5.0 | 220 | 0.7463 | 0.72 | 0.7155 |
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+ | 0.4916 | 6.0 | 264 | 0.7391 | 0.7 | 0.7032 |
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+ | 0.4252 | 7.0 | 308 | 0.7351 | 0.72 | 0.7195 |
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+ | 0.3756 | 8.0 | 352 | 0.7562 | 0.69 | 0.6976 |
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  ### Framework versions
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+ - Transformers 4.33.1
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  - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3
config.json CHANGED
@@ -32,7 +32,7 @@
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.32.1",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 250002
 
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.33.1",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 250002
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