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deberta-financial

Text Classification
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deberta-v2
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text-embeddings-inference
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JoJoLabs/financial-deberta-v1

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  1. README.md +20 -5
  2. logs/events.out.tfevents.1745213071.16d1498ff90a.1.0 +3 -0
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README.md CHANGED
@@ -18,8 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2316
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- - Accuracy: 0.0
 
 
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 4
 
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  ### Training results
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2137
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+ - Accuracy: 0.9146
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+ - Filtered Samples: 0
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+ - Remaining Samples: 2751
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Filtered Samples | Remaining Samples |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:----------------:|:-----------------:|
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+ | 0.4647 | 0.2997 | 232 | 0.3944 | 0.8593 | 0 | 2751 |
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+ | 0.3971 | 0.5995 | 464 | 0.3618 | 0.8582 | 0 | 2751 |
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+ | 0.2951 | 0.8992 | 696 | 0.3034 | 0.8917 | 0 | 2751 |
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+ | 0.2265 | 1.1990 | 928 | 0.2843 | 0.8964 | 0 | 2751 |
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+ | 0.269 | 1.4987 | 1160 | 0.2540 | 0.9059 | 0 | 2751 |
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+ | 0.2077 | 1.7984 | 1392 | 0.2481 | 0.9037 | 0 | 2751 |
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+ | 0.1427 | 2.0982 | 1624 | 0.2283 | 0.9073 | 0 | 2751 |
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+ | 0.1723 | 2.3979 | 1856 | 0.2224 | 0.9124 | 0 | 2751 |
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+ | 0.1759 | 2.6977 | 2088 | 0.2198 | 0.9131 | 0 | 2751 |
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+ | 0.1836 | 2.9974 | 2320 | 0.2137 | 0.9146 | 0 | 2751 |
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  ### Framework versions
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