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Twroberta-baseB_5epoch

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End of training

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  1. README.md +17 -14
  2. model.safetensors +1 -1
  3. runs/Jun08_11-02-50_406ce56e7aa3/events.out.tfevents.1717844571.406ce56e7aa3.1868.0 +3 -0
  4. runs/Jun08_11-03-35_406ce56e7aa3/events.out.tfevents.1717844616.406ce56e7aa3.1868.1 +3 -0
  5. runs/Jun08_11-07-10_406ce56e7aa3/events.out.tfevents.1717844831.406ce56e7aa3.1868.2 +3 -0
  6. runs/Jun08_11-07-10_406ce56e7aa3/events.out.tfevents.1717845069.406ce56e7aa3.1868.3 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -4,9 +4,9 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
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  - precision
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  - recall
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- - f1
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  model-index:
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  - name: Twroberta-baseB_5epoch
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  results: []
@@ -19,11 +19,14 @@ 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-irony](https://huggingface.co/cardiffnlp/twitter-roberta-base-irony) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1414
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- - Accuracy: 0.7971
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- - Precision: 0.2686
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- - Recall: 0.3395
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- - F1: 0.2984
 
 
 
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  ## Model description
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@@ -52,18 +55,18 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 217 | 0.1259 | 0.8571 | 0.0 | 0.0 | 0.0 |
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- | No log | 2.0 | 434 | 0.1252 | 0.8579 | 0.3690 | 0.0185 | 0.0351 |
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- | 0.1645 | 3.0 | 651 | 0.1203 | 0.8414 | 0.2958 | 0.2066 | 0.2431 |
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- | 0.1645 | 4.0 | 868 | 0.1383 | 0.7686 | 0.2221 | 0.3616 | 0.2751 |
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- | 0.0952 | 5.0 | 1085 | 0.1414 | 0.7971 | 0.2686 | 0.3395 | 0.2984 |
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  ### Framework versions
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  - Transformers 4.41.2
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- - Pytorch 2.3.0+cu121
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  - Datasets 2.19.2
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  - Tokenizers 0.19.1
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - f1
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  - precision
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  - recall
 
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  model-index:
11
  - name: Twroberta-baseB_5epoch
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  results: []
 
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  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-irony](https://huggingface.co/cardiffnlp/twitter-roberta-base-irony) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1520
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+ - Accuracy: 0.7793
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+ - F1: 0.2545
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+ - Precision: 0.2289
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+ - Recall: 0.2878
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+ - Precision Sarcastic: 0.3258
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+ - Recall Sarcastic: 0.4
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+ - F1 Sarcastic: 0.3591
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
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+ | No log | 1.0 | 217 | 0.1224 | 0.8571 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 434 | 0.1224 | 0.8686 | 0.2294 | 0.4139 | 0.1587 | 0.6232 | 0.2389 | 0.3454 |
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+ | 0.1581 | 3.0 | 651 | 0.1277 | 0.7979 | 0.2474 | 0.2290 | 0.2694 | 0.3380 | 0.4 | 0.3664 |
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+ | 0.1581 | 4.0 | 868 | 0.1438 | 0.7914 | 0.2503 | 0.2424 | 0.2620 | 0.3137 | 0.3556 | 0.3333 |
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+ | 0.0781 | 5.0 | 1085 | 0.1520 | 0.7793 | 0.2545 | 0.2289 | 0.2878 | 0.3258 | 0.4 | 0.3591 |
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  ### Framework versions
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  - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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  - Datasets 2.19.2
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  - Tokenizers 0.19.1
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