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Ghunghru
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gbert-base

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
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End of training

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Files changed (4) hide show
  1. README.md +56 -16
  2. pytorch_model.bin +1 -1
  3. tokenizer.json +1 -8
  4. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1992
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- - F1: 0.4000
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  ## Model description
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@@ -37,28 +37,68 @@ 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: 4e-06
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.6664 | 1.0 | 189 | 0.6660 | 0.0 |
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- | 0.5942 | 2.0 | 378 | 0.5671 | 0.3750 |
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- | 0.5593 | 3.0 | 567 | 0.8488 | 0.3111 |
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- | 0.6282 | 4.0 | 756 | 0.6896 | 0.4444 |
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- | 0.558 | 5.0 | 945 | 0.8825 | 0.4167 |
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- | 0.5242 | 6.0 | 1134 | 1.0105 | 0.3774 |
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- | 0.4843 | 7.0 | 1323 | 1.1065 | 0.4082 |
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- | 0.3792 | 8.0 | 1512 | 1.1807 | 0.4 |
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- | 0.4005 | 9.0 | 1701 | 1.2279 | 0.3774 |
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- | 0.3909 | 10.0 | 1890 | 1.1992 | 0.4000 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6361
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+ - F1: 0.0
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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-07
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 50
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:---:|
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+ | 0.6805 | 1.0 | 189 | 0.6439 | 0.0 |
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+ | 0.6838 | 2.0 | 378 | 0.6409 | 0.0 |
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+ | 0.6668 | 3.0 | 567 | 0.6376 | 0.0 |
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+ | 0.6666 | 4.0 | 756 | 0.6388 | 0.0 |
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+ | 0.684 | 5.0 | 945 | 0.6372 | 0.0 |
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+ | 0.673 | 6.0 | 1134 | 0.6419 | 0.0 |
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+ | 0.7006 | 7.0 | 1323 | 0.6381 | 0.0 |
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+ | 0.6819 | 8.0 | 1512 | 0.6404 | 0.0 |
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+ | 0.6937 | 9.0 | 1701 | 0.6387 | 0.0 |
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+ | 0.6809 | 10.0 | 1890 | 0.6375 | 0.0 |
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+ | 0.6753 | 11.0 | 2079 | 0.6386 | 0.0 |
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+ | 0.6688 | 12.0 | 2268 | 0.6449 | 0.0 |
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+ | 0.6898 | 13.0 | 2457 | 0.6407 | 0.0 |
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+ | 0.6682 | 14.0 | 2646 | 0.6458 | 0.0 |
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+ | 0.6923 | 15.0 | 2835 | 0.6498 | 0.0 |
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+ | 0.6961 | 16.0 | 3024 | 0.6482 | 0.0 |
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+ | 0.6934 | 17.0 | 3213 | 0.6432 | 0.0 |
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+ | 0.6853 | 18.0 | 3402 | 0.6457 | 0.0 |
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+ | 0.6747 | 19.0 | 3591 | 0.6489 | 0.0 |
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+ | 0.6939 | 20.0 | 3780 | 0.6465 | 0.0 |
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+ | 0.6838 | 21.0 | 3969 | 0.6425 | 0.0 |
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+ | 0.6725 | 22.0 | 4158 | 0.6401 | 0.0 |
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+ | 0.6736 | 23.0 | 4347 | 0.6435 | 0.0 |
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+ | 0.6705 | 24.0 | 4536 | 0.6425 | 0.0 |
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+ | 0.6838 | 25.0 | 4725 | 0.6408 | 0.0 |
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+ | 0.6742 | 26.0 | 4914 | 0.6417 | 0.0 |
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+ | 0.6658 | 27.0 | 5103 | 0.6405 | 0.0 |
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+ | 0.6672 | 28.0 | 5292 | 0.6445 | 0.0 |
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+ | 0.6845 | 29.0 | 5481 | 0.6403 | 0.0 |
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+ | 0.661 | 30.0 | 5670 | 0.6408 | 0.0 |
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+ | 0.6775 | 31.0 | 5859 | 0.6394 | 0.0 |
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+ | 0.6556 | 32.0 | 6048 | 0.6420 | 0.0 |
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+ | 0.6708 | 33.0 | 6237 | 0.6387 | 0.0 |
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+ | 0.6633 | 34.0 | 6426 | 0.6384 | 0.0 |
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+ | 0.6536 | 35.0 | 6615 | 0.6401 | 0.0 |
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+ | 0.6681 | 36.0 | 6804 | 0.6383 | 0.0 |
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+ | 0.6573 | 37.0 | 6993 | 0.6381 | 0.0 |
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+ | 0.6489 | 38.0 | 7182 | 0.6381 | 0.0 |
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+ | 0.6806 | 39.0 | 7371 | 0.6347 | 0.0 |
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+ | 0.6267 | 40.0 | 7560 | 0.6373 | 0.0 |
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+ | 0.6577 | 41.0 | 7749 | 0.6343 | 0.0 |
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+ | 0.6464 | 42.0 | 7938 | 0.6347 | 0.0 |
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+ | 0.6325 | 43.0 | 8127 | 0.6361 | 0.0 |
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+ | 0.6583 | 44.0 | 8316 | 0.6363 | 0.0 |
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+ | 0.6634 | 45.0 | 8505 | 0.6355 | 0.0 |
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+ | 0.6504 | 46.0 | 8694 | 0.6347 | 0.0 |
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+ | 0.6457 | 47.0 | 8883 | 0.6356 | 0.0 |
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+ | 0.632 | 48.0 | 9072 | 0.6362 | 0.0 |
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+ | 0.651 | 49.0 | 9261 | 0.6362 | 0.0 |
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+ | 0.6538 | 50.0 | 9450 | 0.6361 | 0.0 |
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  ### Framework versions
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