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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_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_single_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: 1.0183
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- Accuracy: 0.6218
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- F1: 0.6262
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- Precision: 0.6318
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- Recall: 0.6218
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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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| 1.0456 | 1.0 | 9 | 0.9718 | 0.4958 | 0.4197 | 0.6526 | 0.4958 |
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| 0.9042 | 2.0 | 18 | 0.8920 | 0.5882 | 0.5769 | 0.5784 | 0.5882 |
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| 0.7923 | 3.0 | 27 | 0.8427 | 0.6134 | 0.5861 | 0.5935 | 0.6134 |
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| 0.7544 | 4.0 | 36 | 0.8400 | 0.6387 | 0.6234 | 0.6344 | 0.6387 |
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| 0.6675 | 5.0 | 45 | 0.8410 | 0.6303 | 0.6095 | 0.6184 | 0.6303 |
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| 0.6091 | 6.0 | 54 | 0.9095 | 0.6050 | 0.6041 | 0.6396 | 0.6050 |
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| 0.6279 | 7.0 | 63 | 0.8596 | 0.6723 | 0.6692 | 0.6725 | 0.6723 |
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| 0.4968 | 8.0 | 72 | 0.8725 | 0.6303 | 0.6274 | 0.6253 | 0.6303 |
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| 0.4459 | 9.0 | 81 | 0.9120 | 0.6387 | 0.6395 | 0.6426 | 0.6387 |
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| 0.4122 | 10.0 | 90 | 0.9478 | 0.6303 | 0.6262 | 0.6248 | 0.6303 |
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| 0.3244 | 11.0 | 99 | 0.9746 | 0.6387 | 0.6375 | 0.6381 | 0.6387 |
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| 0.3535 | 12.0 | 108 | 1.0183 | 0.6218 | 0.6262 | 0.6318 | 0.6218 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.12.0+cu113
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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