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AndreiUrsu
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TweetRoberta_5epochs

Text Classification
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End of training

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  1. README.md +11 -9
  2. model.safetensors +1 -1
  3. runs/May02_09-15-23_498e485a9654/events.out.tfevents.1714643438.498e485a9654.318.1 +2 -2
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  6. runs/May02_09-59-37_498e485a9654/events.out.tfevents.1714647490.498e485a9654.318.5 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2870
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- - Accuracy: 0.945
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- - F1: 0.9452
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  ## Model description
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@@ -44,15 +44,17 @@ 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: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.2671 | 1.0 | 2500 | 0.3942 | 0.921 | 0.9168 |
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- | 0.2079 | 2.0 | 5000 | 0.2792 | 0.9384 | 0.9400 |
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- | 0.1376 | 3.0 | 7500 | 0.2870 | 0.945 | 0.9452 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3387
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+ - Accuracy: 0.9452
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+ - F1: 0.9454
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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: 5
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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+ | 0.2755 | 1.0 | 2500 | 0.4153 | 0.9176 | 0.9129 |
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+ | 0.2107 | 2.0 | 5000 | 0.3076 | 0.9312 | 0.9341 |
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+ | 0.1421 | 3.0 | 7500 | 0.2812 | 0.9428 | 0.9424 |
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+ | 0.081 | 4.0 | 10000 | 0.3304 | 0.9464 | 0.9466 |
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+ | 0.0601 | 5.0 | 12500 | 0.3387 | 0.9452 | 0.9454 |
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  ### Framework versions
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