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mirfan899
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hindi-muril-ner

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
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mirfan899 commited on
Commit
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End of training

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Files changed (3) hide show
  1. README.md +10 -10
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5652
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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: 0.9029
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  ## Model description
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@@ -43,7 +43,7 @@ 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: 0.001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -53,10 +53,10 @@ 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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- | 0.6329 | 1.0 | 882 | 0.5652 | 0.0 | 0.0 | 0.0 | 0.9029 |
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- | 0.586 | 2.0 | 1764 | 0.5652 | 0.0 | 0.0 | 0.0 | 0.9029 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0264
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+ - Precision: 0.8961
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+ - Recall: 0.9328
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+ - F1: 0.9141
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+ - Accuracy: 0.9937
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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: 1e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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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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+ | 0.2306 | 1.0 | 882 | 0.0523 | 0.8176 | 0.8724 | 0.8441 | 0.9875 |
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+ | 0.0362 | 2.0 | 1764 | 0.0264 | 0.8961 | 0.9328 | 0.9141 | 0.9937 |
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  ### Framework versions
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