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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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base_model: DeepPavlov/distilrubert-tiny-cased-conversational-v1 |
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model-index: |
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- name: distilrubert-tiny-cased-conversational-v1_finetuned_empathy_classifier |
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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_finetuned_empathy_classifier |
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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: 0.6624 |
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- Accuracy: 0.6780 |
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- F1: 0.6878 |
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- Precision: 0.7175 |
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- Recall: 0.6780 |
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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=0.0001 |
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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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| 1.09 | 1.0 | 9 | 1.0661 | 0.4407 | 0.4464 | 0.6498 | 0.4407 | |
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| 1.0292 | 2.0 | 18 | 0.9658 | 0.5678 | 0.5223 | 0.5179 | 0.5678 | |
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| 0.942 | 3.0 | 27 | 0.8659 | 0.5932 | 0.5807 | 0.5723 | 0.5932 | |
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| 0.8614 | 4.0 | 36 | 0.7864 | 0.6186 | 0.5924 | 0.5879 | 0.6186 | |
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| 0.8002 | 5.0 | 45 | 0.7766 | 0.6017 | 0.5946 | 0.6086 | 0.6017 | |
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| 0.7633 | 6.0 | 54 | 0.7545 | 0.6186 | 0.6022 | 0.6151 | 0.6186 | |
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| 0.7249 | 7.0 | 63 | 0.7649 | 0.6356 | 0.6381 | 0.6921 | 0.6356 | |
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| 0.6687 | 8.0 | 72 | 0.7115 | 0.6695 | 0.6741 | 0.7154 | 0.6695 | |
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| 0.6426 | 9.0 | 81 | 0.6554 | 0.6864 | 0.6761 | 0.6807 | 0.6864 | |
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| 0.6144 | 10.0 | 90 | 0.6649 | 0.6864 | 0.6909 | 0.7172 | 0.6864 | |
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| 0.6252 | 11.0 | 99 | 0.8685 | 0.6186 | 0.6118 | 0.6880 | 0.6186 | |
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| 0.5988 | 12.0 | 108 | 0.6306 | 0.6949 | 0.7015 | 0.7107 | 0.6949 | |
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| 0.56 | 13.0 | 117 | 0.6919 | 0.6610 | 0.6662 | 0.7061 | 0.6610 | |
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| 0.5468 | 14.0 | 126 | 0.6563 | 0.6949 | 0.6980 | 0.7188 | 0.6949 | |
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| 0.5658 | 15.0 | 135 | 0.6351 | 0.6949 | 0.7048 | 0.7280 | 0.6949 | |
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| 0.5262 | 16.0 | 144 | 0.6902 | 0.6780 | 0.6821 | 0.7173 | 0.6780 | |
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| 0.4777 | 17.0 | 153 | 0.6237 | 0.6949 | 0.6981 | 0.7056 | 0.6949 | |
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| 0.4771 | 18.0 | 162 | 0.6688 | 0.6780 | 0.6799 | 0.7035 | 0.6780 | |
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| 0.4737 | 19.0 | 171 | 0.6482 | 0.6864 | 0.6957 | 0.7219 | 0.6864 | |
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| 0.5033 | 20.0 | 180 | 0.6624 | 0.6780 | 0.6878 | 0.7175 | 0.6780 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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