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distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier
mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier
distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier is a text classification model from mmillet. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Jul 25, 2022
- Updated
- Jul 25, 2022
- SHA
- 683570f6
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
distilrubert-tiny-cased-conversational-v1_single_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: 1.0183
- Accuracy: 0.6218
- F1: 0.6262
- Precision: 0.6318
- Recall: 0.6218
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=1e-06
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.0456 | 1.0 | 9 | 0.9718 | 0.4958 | 0.4197 | 0.6526 | 0.4958 |
| 0.9042 | 2.0 | 18 | 0.8920 | 0.5882 | 0.5769 | 0.5784 | 0.5882 |
| 0.7923 | 3.0 | 27 | 0.8427 | 0.6134 | 0.5861 | 0.5935 | 0.6134 |
| 0.7544 | 4.0 | 36 | 0.8400 | 0.6387 | 0.6234 | 0.6344 | 0.6387 |
| 0.6675 | 5.0 | 45 | 0.8410 | 0.6303 | 0.6095 | 0.6184 | 0.6303 |
| 0.6091 | 6.0 | 54 | 0.9095 | 0.6050 | 0.6041 | 0.6396 | 0.6050 |
| 0.6279 | 7.0 | 63 | 0.8596 | 0.6723 | 0.6692 | 0.6725 | 0.6723 |
| 0.4968 | 8.0 | 72 | 0.8725 | 0.6303 | 0.6274 | 0.6253 | 0.6303 |
| 0.4459 | 9.0 | 81 | 0.9120 | 0.6387 | 0.6395 | 0.6426 | 0.6387 |
| 0.4122 | 10.0 | 90 | 0.9478 | 0.6303 | 0.6262 | 0.6248 | 0.6303 |
| 0.3244 | 11.0 | 99 | 0.9746 | 0.6387 | 0.6375 | 0.6381 | 0.6387 |
| 0.3535 | 12.0 | 108 | 1.0183 | 0.6218 | 0.6262 | 0.6318 | 0.6218 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Created
- Jul 25, 2022
- Updated
- Jul 25, 2022