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nattkorat
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trigger_cls

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
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  1. README.md +17 -11
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@@ -6,6 +6,9 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
 
 
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  model-index:
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  - name: trigger_cls
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  results: []
@@ -18,8 +21,11 @@ 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: 0.3421
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- - Accuracy: 0.8935
 
 
 
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  ## Model description
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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: 16
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- - eval_batch_size: 16
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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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 268 | 0.5867 | 0.7542 |
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- | 0.8538 | 2.0 | 536 | 0.3530 | 0.8888 |
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- | 0.8538 | 3.0 | 804 | 0.3836 | 0.8514 |
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- | 0.3121 | 4.0 | 1072 | 0.3208 | 0.8925 |
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- | 0.3121 | 5.0 | 1340 | 0.3421 | 0.8935 |
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  ### Framework versions
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - precision
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+ - recall
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+ - f1
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  model-index:
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  - name: trigger_cls
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  results: []
 
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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: 0.3221
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+ - Accuracy: 0.8876
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+ - Precision: 0.8878
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+ - Recall: 0.8876
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+ - F1: 0.8874
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  ## Model description
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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: 32
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+ - eval_batch_size: 32
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 201 | 0.5449 | 0.8120 | 0.8036 | 0.8120 | 0.7961 |
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+ | No log | 2.0 | 402 | 0.3569 | 0.8757 | 0.8766 | 0.8757 | 0.8736 |
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+ | 0.7649 | 3.0 | 603 | 0.3444 | 0.8826 | 0.8831 | 0.8826 | 0.8822 |
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+ | 0.7649 | 4.0 | 804 | 0.3337 | 0.8832 | 0.8836 | 0.8832 | 0.8830 |
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+ | 0.2524 | 5.0 | 1005 | 0.3221 | 0.8876 | 0.8878 | 0.8876 | 0.8874 |
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  ### Framework versions