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distilrubert-tiny-cased-conversational-v1_finetuned_empathy_classifier
This model is a fine-tuned version of DeepPavlov/distilrubert-tiny-cased-conversational-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6624
- Accuracy: 0.6780
- F1: 0.6878
- Precision: 0.7175
- Recall: 0.6780
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=0.0001
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.09 | 1.0 | 9 | 1.0661 | 0.4407 | 0.4464 | 0.6498 | 0.4407 |
| 1.0292 | 2.0 | 18 | 0.9658 | 0.5678 | 0.5223 | 0.5179 | 0.5678 |
| 0.942 | 3.0 | 27 | 0.8659 | 0.5932 | 0.5807 | 0.5723 | 0.5932 |
| 0.8614 | 4.0 | 36 | 0.7864 | 0.6186 | 0.5924 | 0.5879 | 0.6186 |
| 0.8002 | 5.0 | 45 | 0.7766 | 0.6017 | 0.5946 | 0.6086 | 0.6017 |
| 0.7633 | 6.0 | 54 | 0.7545 | 0.6186 | 0.6022 | 0.6151 | 0.6186 |
| 0.7249 | 7.0 | 63 | 0.7649 | 0.6356 | 0.6381 | 0.6921 | 0.6356 |
| 0.6687 | 8.0 | 72 | 0.7115 | 0.6695 | 0.6741 | 0.7154 | 0.6695 |
| 0.6426 | 9.0 | 81 | 0.6554 | 0.6864 | 0.6761 | 0.6807 | 0.6864 |
| 0.6144 | 10.0 | 90 | 0.6649 | 0.6864 | 0.6909 | 0.7172 | 0.6864 |
| 0.6252 | 11.0 | 99 | 0.8685 | 0.6186 | 0.6118 | 0.6880 | 0.6186 |
| 0.5988 | 12.0 | 108 | 0.6306 | 0.6949 | 0.7015 | 0.7107 | 0.6949 |
| 0.56 | 13.0 | 117 | 0.6919 | 0.6610 | 0.6662 | 0.7061 | 0.6610 |
| 0.5468 | 14.0 | 126 | 0.6563 | 0.6949 | 0.6980 | 0.7188 | 0.6949 |
| 0.5658 | 15.0 | 135 | 0.6351 | 0.6949 | 0.7048 | 0.7280 | 0.6949 |
| 0.5262 | 16.0 | 144 | 0.6902 | 0.6780 | 0.6821 | 0.7173 | 0.6780 |
| 0.4777 | 17.0 | 153 | 0.6237 | 0.6949 | 0.6981 | 0.7056 | 0.6949 |
| 0.4771 | 18.0 | 162 | 0.6688 | 0.6780 | 0.6799 | 0.7035 | 0.6780 |
| 0.4737 | 19.0 | 171 | 0.6482 | 0.6864 | 0.6957 | 0.7219 | 0.6864 |
| 0.5033 | 20.0 | 180 | 0.6624 | 0.6780 | 0.6878 | 0.7175 | 0.6780 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
