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xlm-roberta-base-finetuned-wol

Token Classification
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PyTorch
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xlm-roberta
Generated from Trainer
Eval Results
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Training completed!

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  1. README.md +9 -10
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.8143486469477659
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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 masakhaner2 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0663
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- - F1: 0.8143
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 48
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- - eval_batch_size: 48
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 1.0 | 96 | 0.1062 | 0.6522 |
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- | 0.1995 | 2.0 | 192 | 0.0733 | 0.7662 |
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- | 0.1995 | 3.0 | 288 | 0.0681 | 0.8065 |
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- | 0.0549 | 4.0 | 384 | 0.0663 | 0.8143 |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.7235926628716003
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the masakhaner2 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0815
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+ - F1: 0.7236
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 72 | 0.1272 | 0.5887 |
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+ | 0.2412 | 2.0 | 144 | 0.0916 | 0.6888 |
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+ | 0.2412 | 3.0 | 216 | 0.0815 | 0.7236 |
 
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  ### Framework versions
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