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xlm-roberta-base-finetuned-panx-de

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Training complete!

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Files changed (4) hide show
  1. README.md +2 -16
  2. model.safetensors +1 -1
  3. runs/Nov18_11-37-41_Rays-MacBook-Pro.local/events.out.tfevents.1731901356.Rays-MacBook-Pro.local.97459.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -4,8 +4,6 @@ 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:
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- - f1
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  model-index:
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  - name: xlm-roberta-base-finetuned-panx-de
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  results: []
@@ -17,9 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
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  # xlm-roberta-base-finetuned-panx-de
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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: 0.1395
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- - F1: 0.8600
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  ## Model description
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@@ -42,22 +37,13 @@ The following hyperparameters were used during training:
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  - train_batch_size: 24
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  - eval_batch_size: 8
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  - seed: 42
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- - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 3
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.2542 | 1.0 | 525 | 0.1634 | 0.8225 |
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- | 0.1277 | 2.0 | 1050 | 0.1359 | 0.8527 |
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- | 0.0795 | 3.0 | 1575 | 0.1395 | 0.8600 |
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-
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-
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  ### Framework versions
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  - Transformers 4.46.2
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- - Pytorch 2.5.1+cu121
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  - Datasets 3.1.0
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  - Tokenizers 0.20.3
 
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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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  model-index:
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  - name: xlm-roberta-base-finetuned-panx-de
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  results: []
 
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  # xlm-roberta-base-finetuned-panx-de
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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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  ## Model description
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  - train_batch_size: 24
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  - eval_batch_size: 8
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  - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 3
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  ### Framework versions
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  - Transformers 4.46.2
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+ - Pytorch 2.5.1
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  - Datasets 3.1.0
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  - Tokenizers 0.20.3
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