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stulcrad
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CNEC2_0_Supertypes_xlm-roberta-large

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xlm-roberta
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  1. README.md +15 -15
  2. model.safetensors +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.8473042109405746
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  - name: Recall
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  type: recall
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- value: 0.889301941346551
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  - name: F1
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  type: f1
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- value: 0.867795243853285
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  - name: Accuracy
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  type: accuracy
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- value: 0.9698392003476749
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1673
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- - Precision: 0.8473
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- - Recall: 0.8893
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- - F1: 0.8678
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- - Accuracy: 0.9698
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  ## Model description
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@@ -67,7 +67,7 @@ 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: 1
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  - eval_batch_size: 1
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  - seed: 42
@@ -77,11 +77,11 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.2246 | 1.0 | 7193 | 0.1918 | 0.8122 | 0.8505 | 0.8309 | 0.9616 |
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- | 0.1431 | 2.0 | 14386 | 0.1665 | 0.8241 | 0.8748 | 0.8487 | 0.9671 |
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- | 0.0845 | 3.0 | 21579 | 0.1673 | 0.8473 | 0.8893 | 0.8678 | 0.9698 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.0
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  - name: Recall
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  type: recall
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+ value: 0.0
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  - name: F1
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  type: f1
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+ value: 0.0
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7809647979139505
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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 [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9843
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+ - Precision: 0.0
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+ - Recall: 0.0
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+ - F1: 0.0
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+ - Accuracy: 0.7810
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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: 0.005
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  - train_batch_size: 1
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  - eval_batch_size: 1
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  - seed: 42
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
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+ | 1.0475 | 1.0 | 7193 | 0.9939 | 0.0 | 0.0 | 0.0 | 0.7810 |
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+ | 0.9691 | 2.0 | 14386 | 0.9840 | 0.0 | 0.0 | 0.0 | 0.7810 |
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+ | 0.9341 | 3.0 | 21579 | 0.9843 | 0.0 | 0.0 | 0.0 | 0.7810 |
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  ### Framework versions
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