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Ludo33
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e5_Eau_Multilabel_Topic_Sentiment

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End of training

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  1. README.md +9 -9
  2. classifier.pt +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [intfloat/multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2356
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- - F1 Topic: 0.9113
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- - F1 Sentiment: 0.8898
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- - F1 Macro Avg: 0.9005
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  ## Model description
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  ### Training hyperparameters
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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: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -54,10 +54,10 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 Topic | F1 Sentiment | F1 Macro Avg |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:------------:|
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- | 0.9732 | 1.0 | 148 | 0.4898 | 0.7662 | 0.7817 | 0.7740 |
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- | 0.3646 | 2.0 | 296 | 0.2792 | 0.8826 | 0.8688 | 0.8757 |
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- | 0.2033 | 3.0 | 444 | 0.2304 | 0.9078 | 0.8870 | 0.8974 |
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- | 0.1546 | 4.0 | 592 | 0.2356 | 0.9113 | 0.8898 | 0.9005 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [intfloat/multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2357
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+ - F1 Topic: 0.9099
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+ - F1 Sentiment: 0.8779
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+ - F1 Macro Avg: 0.8939
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 Topic | F1 Sentiment | F1 Macro Avg |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:------------:|
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+ | 1.0863 | 1.0 | 148 | 0.8031 | 0.5733 | 0.6922 | 0.6328 |
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+ | 0.5734 | 2.0 | 296 | 0.3777 | 0.8058 | 0.8242 | 0.8150 |
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+ | 0.2858 | 3.0 | 444 | 0.2523 | 0.8957 | 0.8652 | 0.8805 |
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+ | 0.2023 | 4.0 | 592 | 0.2357 | 0.9099 | 0.8779 | 0.8939 |
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  ### Framework versions
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