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@@ -17,7 +17,8 @@ pipeline_tag: text-classification
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  # fnet-base-Financial_Sentiment_Analysis
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- This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base) on the None dataset.
 
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  It achieves the following results on the evaluation set:
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  - Loss: 0.3281
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  - Accuracy: 0.8117
@@ -62,7 +63,7 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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  | 0.6116 | 1.0 | 134 | 0.5127 | 0.6304 | 0.5606 | 0.6304 | 0.4705 | 0.6304 | 0.6304 | 0.5272 | 0.6722 | 0.6304 | 0.6103 |
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  | 0.4497 | 2.0 | 268 | 0.3885 | 0.7578 | 0.7490 | 0.7578 | 0.6783 | 0.7578 | 0.7578 | 0.6636 | 0.7677 | 0.7578 | 0.7196 |
 
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  # fnet-base-Financial_Sentiment_Analysis
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+ This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base).
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+
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  It achieves the following results on the evaluation set:
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  - Loss: 0.3281
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  - Accuracy: 0.8117
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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  | 0.6116 | 1.0 | 134 | 0.5127 | 0.6304 | 0.5606 | 0.6304 | 0.4705 | 0.6304 | 0.6304 | 0.5272 | 0.6722 | 0.6304 | 0.6103 |
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  | 0.4497 | 2.0 | 268 | 0.3885 | 0.7578 | 0.7490 | 0.7578 | 0.6783 | 0.7578 | 0.7578 | 0.6636 | 0.7677 | 0.7578 | 0.7196 |