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--- |
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license: mit |
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base_model: microsoft/deberta-v3-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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- f1 |
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model-index: |
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- name: deberta-v3-ft-news-sentiment-analisys |
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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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# deberta-v3-ft-news-sentiment-analisys |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1175 |
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- Precision: 0.9780 |
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- Recall: 0.9780 |
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- Accuracy: 0.9780 |
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- F1: 0.9780 |
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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: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:| |
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| No log | 1.0 | 64 | 0.3711 | 0.8282 | 0.8282 | 0.8282 | 0.8282 | |
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| No log | 2.0 | 128 | 0.1800 | 0.9559 | 0.9559 | 0.9559 | 0.9559 | |
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| No log | 3.0 | 192 | 0.1296 | 0.9604 | 0.9604 | 0.9604 | 0.9604 | |
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| No log | 4.0 | 256 | 0.1228 | 0.9736 | 0.9736 | 0.9736 | 0.9736 | |
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| No log | 5.0 | 320 | 0.1352 | 0.9736 | 0.9736 | 0.9736 | 0.9736 | |
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| No log | 6.0 | 384 | 0.1785 | 0.9648 | 0.9648 | 0.9648 | 0.9648 | |
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| No log | 7.0 | 448 | 0.1175 | 0.9780 | 0.9780 | 0.9780 | 0.9780 | |
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| 0.1612 | 8.0 | 512 | 0.1344 | 0.9692 | 0.9692 | 0.9692 | 0.9692 | |
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| 0.1612 | 9.0 | 576 | 0.1274 | 0.9648 | 0.9648 | 0.9648 | 0.9648 | |
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| 0.1612 | 10.0 | 640 | 0.1242 | 0.9692 | 0.9692 | 0.9692 | 0.9692 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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