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marcelomoreno26
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deberta-v3-base-rotten-tomatoes

Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +10 -9
  2. model.safetensors +1 -1
  3. 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 [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3230
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- - F1: 0.9137
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 7.5e-06
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.3545 | 1.0 | 534 | 0.2959 | 0.8946 |
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- | 0.2185 | 2.0 | 1068 | 0.3097 | 0.9174 |
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- | 0.1664 | 3.0 | 1602 | 0.3374 | 0.9128 |
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- | 0.119 | 4.0 | 2136 | 0.4510 | 0.9042 |
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- | 0.09 | 5.0 | 2670 | 0.5311 | 0.9004 |
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2619
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+ - F1: 0.9184
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 7.5e-06
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 267 | 0.2430 | 0.9146 |
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+ | 0.3091 | 2.0 | 534 | 0.2499 | 0.9156 |
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+ | 0.3091 | 3.0 | 801 | 0.2829 | 0.9174 |
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+ | 0.1496 | 4.0 | 1068 | 0.2742 | 0.9137 |
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+ | 0.1496 | 5.0 | 1335 | 0.3845 | 0.9099 |
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+ | 0.0864 | 6.0 | 1602 | 0.4254 | 0.9024 |
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  ### Framework versions
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