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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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- precision |
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- recall |
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model-index: |
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- name: distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented |
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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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# distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented |
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This model is a fine-tuned version of [DeepPavlov/distilrubert-tiny-cased-conversational-v1](https://huggingface.co/DeepPavlov/distilrubert-tiny-cased-conversational-v1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5908 |
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- Accuracy: 0.8653 |
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- F1: 0.8656 |
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- Precision: 0.8665 |
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- Recall: 0.8653 |
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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: 0.0001 |
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- train_batch_size: 64 |
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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-06 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.9172 | 1.0 | 69 | 0.5124 | 0.8246 | 0.8220 | 0.8271 | 0.8246 | |
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| 0.4709 | 2.0 | 138 | 0.4279 | 0.8528 | 0.8505 | 0.8588 | 0.8528 | |
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| 0.3194 | 3.0 | 207 | 0.3770 | 0.8737 | 0.8727 | 0.8740 | 0.8737 | |
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| 0.2459 | 4.0 | 276 | 0.3951 | 0.8685 | 0.8682 | 0.8692 | 0.8685 | |
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| 0.1824 | 5.0 | 345 | 0.4005 | 0.8831 | 0.8834 | 0.8841 | 0.8831 | |
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| 0.1515 | 6.0 | 414 | 0.4356 | 0.8800 | 0.8797 | 0.8801 | 0.8800 | |
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| 0.1274 | 7.0 | 483 | 0.4642 | 0.8727 | 0.8726 | 0.8731 | 0.8727 | |
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| 0.0833 | 8.0 | 552 | 0.5226 | 0.8633 | 0.8627 | 0.8631 | 0.8633 | |
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| 0.073 | 9.0 | 621 | 0.5327 | 0.8695 | 0.8686 | 0.8692 | 0.8695 | |
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| 0.0575 | 10.0 | 690 | 0.5908 | 0.8653 | 0.8656 | 0.8665 | 0.8653 | |
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### Framework versions |
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- Transformers 4.19.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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