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--- |
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tags: |
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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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model-index: |
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- name: finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED |
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This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2741 |
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- Accuracy: 0.7475 |
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- F1: 0.7253 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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- seed: 42 |
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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: 16 |
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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 | 1.0 | 249 | 0.9150 | 0.7346 | 0.6484 | |
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| No log | 2.0 | 498 | 0.8837 | 0.6210 | 0.6317 | |
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| 1.033 | 3.0 | 747 | 0.8460 | 0.6485 | 0.6666 | |
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| 1.033 | 4.0 | 996 | 1.0089 | 0.6831 | 0.6909 | |
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| 0.5642 | 5.0 | 1245 | 1.2507 | 0.7352 | 0.7152 | |
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| 0.5642 | 6.0 | 1494 | 1.3241 | 0.7129 | 0.7042 | |
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| 0.2078 | 7.0 | 1743 | 1.5163 | 0.7528 | 0.7230 | |
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| 0.2078 | 8.0 | 1992 | 1.5818 | 0.7352 | 0.7236 | |
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| 0.1108 | 9.0 | 2241 | 1.7930 | 0.7012 | 0.7046 | |
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| 0.1108 | 10.0 | 2490 | 1.8262 | 0.7305 | 0.7211 | |
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| 0.07 | 11.0 | 2739 | 2.0415 | 0.7440 | 0.7192 | |
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| 0.07 | 12.0 | 2988 | 2.1260 | 0.7563 | 0.7230 | |
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| 0.0392 | 13.0 | 3237 | 2.1502 | 0.7528 | 0.7323 | |
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| 0.0392 | 14.0 | 3486 | 2.2117 | 0.7516 | 0.7270 | |
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| 0.0174 | 15.0 | 3735 | 2.2657 | 0.7405 | 0.7236 | |
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| 0.0174 | 16.0 | 3984 | 2.2741 | 0.7475 | 0.7253 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.9.1 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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