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sentiment_DiceLoss

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  1. README.md +33 -5
  2. model.safetensors +1 -1
  3. runs/Jun04_05-52-50_2633a01a23c9/events.out.tfevents.1717480376.2633a01a23c9.2417.0 +3 -0
  4. runs/Jun04_05-52-50_2633a01a23c9/events.out.tfevents.1717481127.2633a01a23c9.2417.1 +3 -0
  5. 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 [ahmedrachid/FinancialBERT-Sentiment-Analysis](https://huggingface.co/ahmedrachid/FinancialBERT-Sentiment-Analysis) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.8374
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- - Accuracy: 0.8171
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- - F1: 0.7866
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  ## Model description
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@@ -46,15 +46,43 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 32
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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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  ### Framework versions
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  - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [ahmedrachid/FinancialBERT-Sentiment-Analysis](https://huggingface.co/ahmedrachid/FinancialBERT-Sentiment-Analysis) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5153
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+ - Accuracy: 0.8683
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+ - F1: 0.8376
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  ## Model description
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  - total_train_batch_size: 32
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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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+ | No log | 0.1739 | 50 | 0.5234 | 0.8096 | 0.7723 |
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+ | No log | 0.3478 | 100 | 0.4390 | 0.8457 | 0.8151 |
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+ | No log | 0.5217 | 150 | 0.4168 | 0.8491 | 0.8137 |
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+ | No log | 0.6957 | 200 | 0.4252 | 0.8522 | 0.8150 |
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+ | No log | 0.8696 | 250 | 0.3931 | 0.8561 | 0.8196 |
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+ | No log | 1.0435 | 300 | 0.4409 | 0.8409 | 0.8118 |
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+ | No log | 1.2174 | 350 | 0.4108 | 0.8657 | 0.8271 |
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+ | No log | 1.3913 | 400 | 0.4382 | 0.8613 | 0.8292 |
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+ | No log | 1.5652 | 450 | 0.4147 | 0.8622 | 0.8287 |
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+ | 0.415 | 1.7391 | 500 | 0.4069 | 0.8652 | 0.8331 |
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+ | 0.415 | 1.9130 | 550 | 0.4170 | 0.8591 | 0.8275 |
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+ | 0.415 | 2.0870 | 600 | 0.4533 | 0.8626 | 0.8296 |
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+ | 0.415 | 2.2609 | 650 | 0.4613 | 0.87 | 0.8401 |
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+ | 0.415 | 2.4348 | 700 | 0.4531 | 0.8770 | 0.8447 |
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+ | 0.415 | 2.6087 | 750 | 0.4534 | 0.8583 | 0.8277 |
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+ | 0.415 | 2.7826 | 800 | 0.4756 | 0.8570 | 0.8274 |
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+ | 0.415 | 2.9565 | 850 | 0.4482 | 0.8683 | 0.8391 |
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+ | 0.415 | 3.1304 | 900 | 0.4858 | 0.8665 | 0.8350 |
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+ | 0.415 | 3.3043 | 950 | 0.4873 | 0.8639 | 0.8341 |
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+ | 0.1812 | 3.4783 | 1000 | 0.5153 | 0.8683 | 0.8376 |
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+ | 0.1812 | 3.6522 | 1050 | 0.5345 | 0.8578 | 0.8281 |
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+ | 0.1812 | 3.8261 | 1100 | 0.5372 | 0.8609 | 0.8331 |
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+ | 0.1812 | 4.0 | 1150 | 0.5172 | 0.8670 | 0.8379 |
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+ | 0.1812 | 4.1739 | 1200 | 0.5643 | 0.8643 | 0.8342 |
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+ | 0.1812 | 4.3478 | 1250 | 0.5783 | 0.8622 | 0.8326 |
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+ | 0.1812 | 4.5217 | 1300 | 0.5909 | 0.8565 | 0.8273 |
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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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