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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Sentiment-Analysis-Model |
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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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# Sentiment-Analysis-Model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6227 |
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- F1 Score: 0.7304 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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 | F1 Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.7461 | 0.5 | 500 | 0.7528 | 0.6523 | |
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| 0.6845 | 1.0 | 1000 | 0.6425 | 0.7132 | |
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| 0.5729 | 1.5 | 1500 | 0.6463 | 0.7415 | |
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| 0.5674 | 2.0 | 2000 | 0.6227 | 0.7304 | |
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| 0.41 | 2.5 | 2500 | 0.9091 | 0.7335 | |
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| 0.4017 | 3.0 | 3000 | 0.8304 | 0.7360 | |
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| 0.2691 | 3.5 | 3500 | 1.2177 | 0.7202 | |
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| 0.3128 | 4.0 | 4000 | 1.1197 | 0.7376 | |
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| 0.197 | 4.5 | 4500 | 1.2951 | 0.7341 | |
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| 0.1887 | 5.0 | 5000 | 1.4508 | 0.7239 | |
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| 0.11 | 5.5 | 5500 | 1.5447 | 0.7203 | |
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| 0.1462 | 6.0 | 6000 | 1.4909 | 0.7383 | |
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| 0.0907 | 6.5 | 6500 | 1.4809 | 0.7332 | |
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| 0.089 | 7.0 | 7000 | 1.7191 | 0.7244 | |
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| 0.0613 | 7.5 | 7500 | 1.7725 | 0.7294 | |
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| 0.0665 | 8.0 | 8000 | 1.8083 | 0.7290 | |
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| 0.0458 | 8.5 | 8500 | 1.8297 | 0.7346 | |
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| 0.0395 | 9.0 | 9000 | 1.8853 | 0.7304 | |
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| 0.0287 | 9.5 | 9500 | 1.9684 | 0.7273 | |
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| 0.0204 | 10.0 | 10000 | 1.9919 | 0.7308 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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