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roberta-base-bne-finetuned-multi-sentiment-finetuned-multi-sentiment

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  1. README.md +15 -7
  2. model.safetensors +1 -1
README.md CHANGED
@@ -6,19 +6,19 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: roberta-base-bne-finetuned-multi-sentiment
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # roberta-base-bne-finetuned-multi-sentiment
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  This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7084
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- - Accuracy: 0.6574
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  ## Model description
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@@ -43,14 +43,22 @@ The following hyperparameters were used during training:
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.7936 | 1.0 | 115 | 0.7396 | 0.6667 |
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- | 0.5753 | 2.0 | 230 | 0.7084 | 0.6574 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: roberta-base-bne-finetuned-multi-sentiment-finetuned-multi-sentiment
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # roberta-base-bne-finetuned-multi-sentiment-finetuned-multi-sentiment
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  This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.0249
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+ - Accuracy: 0.6451
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  ## Model description
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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 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5534 | 1.0 | 115 | 0.7764 | 0.6512 |
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+ | 0.3479 | 2.0 | 230 | 0.9324 | 0.6512 |
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+ | 0.0922 | 3.0 | 345 | 1.2452 | 0.6574 |
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+ | 0.0218 | 4.0 | 460 | 1.7006 | 0.6512 |
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+ | 0.001 | 5.0 | 575 | 1.7949 | 0.6512 |
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+ | 0.0007 | 6.0 | 690 | 1.8798 | 0.6605 |
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+ | 0.0006 | 7.0 | 805 | 1.9510 | 0.6451 |
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+ | 0.0005 | 8.0 | 920 | 1.9926 | 0.6451 |
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+ | 0.0004 | 9.0 | 1035 | 2.0169 | 0.6451 |
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+ | 0.0004 | 10.0 | 1150 | 2.0249 | 0.6451 |
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  ### Framework versions
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