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mrm8488
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deberta-v3-ft-financial-news-sentiment-analysis

Text Classification
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deberta-v2
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  1. README.md +12 -12
  2. model.safetensors +1 -1
  3. runs/Jan21_16-23-35_73095be6df3d/events.out.tfevents.1705854223.73095be6df3d.20744.0 +3 -0
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  5. runs/Jan21_16-29-25_73095be6df3d/events.out.tfevents.1705854576.73095be6df3d.23631.0 +3 -0
  6. runs/Jan21_16-31-00_73095be6df3d/events.out.tfevents.1705854661.73095be6df3d.24267.0 +3 -0
  7. runs/Jan21_16-31-00_73095be6df3d/events.out.tfevents.1705854868.73095be6df3d.24267.1 +3 -0
  8. training_args.bin +1 -1
README.md CHANGED
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # deberta-v3-ft-news-sentiment-analisys
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- This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1107
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- - Precision: 0.9780
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- - Recall: 0.9780
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- - Accuracy: 0.9780
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- - F1: 0.9780
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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: 64
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
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- | No log | 1.0 | 64 | 0.4196 | 0.7885 | 0.7885 | 0.7885 | 0.7885 |
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- | No log | 2.0 | 128 | 0.2166 | 0.9515 | 0.9515 | 0.9515 | 0.9515 |
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- | No log | 3.0 | 192 | 0.1431 | 0.9604 | 0.9604 | 0.9604 | 0.9604 |
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- | No log | 4.0 | 256 | 0.1107 | 0.9780 | 0.9780 | 0.9780 | 0.9780 |
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- | No log | 5.0 | 320 | 0.1292 | 0.9692 | 0.9692 | 0.9692 | 0.9692 |
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  ### Framework versions
 
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  # deberta-v3-ft-news-sentiment-analisys
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+ This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0233
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+ - Precision: 0.9940
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+ - Recall: 0.9940
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+ - Accuracy: 0.9940
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+ - F1: 0.9940
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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: 64
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  - eval_batch_size: 64
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
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+ | No log | 1.0 | 214 | 0.1865 | 0.9323 | 0.9323 | 0.9323 | 0.9323 |
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+ | No log | 2.0 | 428 | 0.0742 | 0.9771 | 0.9771 | 0.9771 | 0.9771 |
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+ | 0.2737 | 3.0 | 642 | 0.0479 | 0.9855 | 0.9855 | 0.9855 | 0.9855 |
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+ | 0.2737 | 4.0 | 856 | 0.0284 | 0.9923 | 0.9923 | 0.9923 | 0.9923 |
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+ | 0.0586 | 5.0 | 1070 | 0.0233 | 0.9940 | 0.9940 | 0.9940 | 0.9940 |
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  ### Framework versions
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