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academic_text_classifier_de

Text Classification
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Safetensors
German
xlm-roberta
Generated from Trainer
text-embeddings-inference
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c-ho/academic_main_text_classifier_de

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  1. README.md +12 -12
README.md CHANGED
@@ -21,11 +21,11 @@ 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-base](https://huggingface.co/FacebookAI/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: 0.2835
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- - Accuracy: 0.9319
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- - Precision: 0.9319
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- - Recall: 0.9319
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- - F1: 0.9319
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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: 5e-05
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- - train_batch_size: 32
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  - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.8491 | 1.0 | 268 | 0.3697 | 0.8858 | 0.8858 | 0.8858 | 0.8858 |
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- | 0.4033 | 2.0 | 536 | 0.3948 | 0.8946 | 0.8946 | 0.8946 | 0.8946 |
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- | 0.2694 | 3.0 | 804 | 0.3032 | 0.9193 | 0.9193 | 0.9193 | 0.9193 |
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- | 0.1998 | 4.0 | 1072 | 0.2782 | 0.9315 | 0.9315 | 0.9315 | 0.9315 |
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- | 0.1549 | 5.0 | 1340 | 0.2835 | 0.9319 | 0.9319 | 0.9319 | 0.9319 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/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: 0.2560
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+ - Accuracy: 0.9245
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+ - Precision: 0.9245
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+ - Recall: 0.9245
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+ - F1: 0.9245
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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: 2e-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: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 
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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 | 134 | 0.6173 | 0.7627 | 0.7627 | 0.7627 | 0.7627 |
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+ | 0.9527 | 2.0 | 268 | 0.4141 | 0.8811 | 0.8811 | 0.8811 | 0.8811 |
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+ | 0.4191 | 3.0 | 402 | 0.3220 | 0.8965 | 0.8965 | 0.8965 | 0.8965 |
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+ | 0.4191 | 4.0 | 536 | 0.2663 | 0.9175 | 0.9175 | 0.9175 | 0.9175 |
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+ | 0.2567 | 5.0 | 670 | 0.2560 | 0.9245 | 0.9245 | 0.9245 | 0.9245 |
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  ### Framework versions