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TenaliAI-FinTech-v1

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

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  1. README.md +26 -26
  2. model.safetensors +1 -1
  3. runs/Nov25_22-34-31_SuperWhite/events.out.tfevents.1732554272.SuperWhite.17418.0 +3 -0
  4. runs/Nov25_22-34-31_SuperWhite/events.out.tfevents.1732578596.SuperWhite.17418.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8406
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  ## Model description
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@@ -47,31 +47,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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- | 2.3809 | 1.0 | 3852 | 1.9607 |
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- | 1.2279 | 2.0 | 7704 | 1.1452 |
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- | 0.9366 | 3.0 | 11556 | 0.9717 |
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- | 0.8443 | 4.0 | 15408 | 0.8946 |
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- | 0.795 | 5.0 | 19260 | 0.8747 |
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- | 0.736 | 6.0 | 23112 | 0.8618 |
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- | 0.7126 | 7.0 | 26964 | 0.8406 |
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- | 0.6937 | 8.0 | 30816 | 0.8497 |
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- | 0.6922 | 9.0 | 34668 | 0.8473 |
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- | 0.6521 | 10.0 | 38520 | 0.8563 |
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- | 0.6838 | 11.0 | 42372 | 0.8638 |
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- | 0.6395 | 12.0 | 46224 | 0.8615 |
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- | 0.6551 | 13.0 | 50076 | 0.8654 |
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- | 0.6038 | 14.0 | 53928 | 0.8795 |
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- | 0.6177 | 15.0 | 57780 | 0.8782 |
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- | 0.6164 | 16.0 | 61632 | 0.8914 |
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- | 0.6071 | 17.0 | 65484 | 0.8859 |
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- | 0.6125 | 18.0 | 69336 | 0.8921 |
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- | 0.6115 | 19.0 | 73188 | 0.8944 |
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- | 0.608 | 20.0 | 77040 | 0.9040 |
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- | 0.5943 | 21.0 | 80892 | 0.9133 |
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- | 0.632 | 22.0 | 84744 | 0.9031 |
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- | 0.6245 | 23.0 | 88596 | 0.9139 |
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- | 0.6094 | 24.0 | 92448 | 0.8965 |
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- | 0.6247 | 25.0 | 96300 | 0.9290 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8172
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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+ | 2.2269 | 1.0 | 3787 | 1.9074 |
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+ | 1.2027 | 2.0 | 7574 | 1.1338 |
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+ | 0.9803 | 3.0 | 11361 | 0.9422 |
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+ | 0.8588 | 4.0 | 15148 | 0.8633 |
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+ | 0.7919 | 5.0 | 18935 | 0.8463 |
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+ | 0.7237 | 6.0 | 22722 | 0.8219 |
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+ | 0.7398 | 7.0 | 26509 | 0.8172 |
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+ | 0.6788 | 8.0 | 30296 | 0.8230 |
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+ | 0.6563 | 9.0 | 34083 | 0.8261 |
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+ | 0.6689 | 10.0 | 37870 | 0.8181 |
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+ | 0.6707 | 11.0 | 41657 | 0.8293 |
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+ | 0.6694 | 12.0 | 45444 | 0.8441 |
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+ | 0.6334 | 13.0 | 49231 | 0.8555 |
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+ | 0.6309 | 14.0 | 53018 | 0.8435 |
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+ | 0.6522 | 15.0 | 56805 | 0.8503 |
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+ | 0.6382 | 16.0 | 60592 | 0.8565 |
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+ | 0.6562 | 17.0 | 64379 | 0.8590 |
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+ | 0.617 | 18.0 | 68166 | 0.8714 |
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+ | 0.6214 | 19.0 | 71953 | 0.8745 |
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+ | 0.6097 | 20.0 | 75740 | 0.8850 |
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+ | 0.6162 | 21.0 | 79527 | 0.8714 |
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+ | 0.6183 | 22.0 | 83314 | 0.8729 |
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+ | 0.6257 | 23.0 | 87101 | 0.8824 |
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+ | 0.6056 | 24.0 | 90888 | 0.8776 |
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+ | 0.5898 | 25.0 | 94675 | 0.8926 |
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  ### Framework versions
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