DeepaPeri commited on
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Training completed!

Browse files
README.md CHANGED
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  ---
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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:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # xlm-roberta-base-finetuned-panx-hi-5-epochs
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- This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2613
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- - F1: 0.8754
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  ## Model description
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@@ -49,11 +49,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.6344 | 1.0 | 168 | 0.3653 | 0.7603 |
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- | 0.2824 | 2.0 | 336 | 0.3270 | 0.8206 |
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- | 0.2056 | 3.0 | 504 | 0.2708 | 0.8539 |
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- | 0.1373 | 4.0 | 672 | 0.2634 | 0.8657 |
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- | 0.0962 | 5.0 | 840 | 0.2613 | 0.8754 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: DeepaPeri/xlm-roberta-base-finetuned-panx-hi-5-epochs
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # xlm-roberta-base-finetuned-panx-hi-5-epochs
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+ This model is a fine-tuned version of [DeepaPeri/xlm-roberta-base-finetuned-panx-hi-5-epochs](https://huggingface.co/DeepaPeri/xlm-roberta-base-finetuned-panx-hi-5-epochs) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2936
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+ - F1: 0.8848
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.168 | 1.0 | 168 | 0.3044 | 0.8586 |
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+ | 0.1187 | 2.0 | 336 | 0.2836 | 0.8640 |
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+ | 0.0848 | 3.0 | 504 | 0.2728 | 0.8800 |
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+ | 0.0528 | 4.0 | 672 | 0.2969 | 0.8959 |
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+ | 0.0308 | 5.0 | 840 | 0.2936 | 0.8848 |
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  ### Framework versions
config.json CHANGED
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  {
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- "_name_or_path": "xlm-roberta-base",
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  "architectures": [
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  "XLMRobertaForTokenClassification"
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  ],
 
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  {
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+ "_name_or_path": "DeepaPeri/xlm-roberta-base-finetuned-panx-hi-5-epochs",
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  "architectures": [
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  "XLMRobertaForTokenClassification"
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  ],
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