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germanic_antielite

Text Classification
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bert
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text-embeddings-inference
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End of training

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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. runs/Nov26_01-23-34_6921bf48f74f/events.out.tfevents.1732584217.6921bf48f74f.1996.0 +2 -2
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2980
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- - Accuracy: 0.9076
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- - F1: 0.4851
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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 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 Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.2286 | 1.0 | 351 | 0.2263 | 0.9090 | 0.4990 |
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- | 0.1729 | 2.0 | 702 | 0.3197 | 0.9065 | 0.3105 |
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- | 0.1106 | 3.0 | 1053 | 0.2980 | 0.9076 | 0.4851 |
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  ### Framework versions
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  - Transformers 4.46.2
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- - Pytorch 2.5.0+cu121
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  - Datasets 3.1.0
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  - Tokenizers 0.20.3
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3430
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+ - Accuracy: 0.9133
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+ - F1: 0.5207
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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 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 Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.2445 | 1.0 | 701 | 0.2310 | 0.8998 | 0.5371 |
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+ | 0.1631 | 2.0 | 1402 | 0.3426 | 0.9105 | 0.3741 |
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+ | 0.0963 | 3.0 | 2103 | 0.3430 | 0.9133 | 0.5207 |
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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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