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README.md
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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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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
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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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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 |
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