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distilrubert-tiny-cased-conversational-v1_finetuned_emotion_experiment_augmented_anger_fear

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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_finetuned_emotion_experiment_augmented_anger_fear
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+ results: []
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+ ---
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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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+
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+ # distilrubert-tiny-cased-conversational-v1_finetuned_emotion_experiment_augmented_anger_fear
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+
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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: 0.3760
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+ - Accuracy: 0.8758
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+ - F1: 0.8750
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+ - Precision: 0.8753
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+ - Recall: 0.8758
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.2636 | 1.0 | 69 | 1.0914 | 0.6013 | 0.5599 | 0.5780 | 0.6013 |
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+ | 1.029 | 2.0 | 138 | 0.9180 | 0.6514 | 0.6344 | 0.6356 | 0.6514 |
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+ | 0.904 | 3.0 | 207 | 0.8235 | 0.6827 | 0.6588 | 0.6904 | 0.6827 |
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+ | 0.8084 | 4.0 | 276 | 0.7272 | 0.7537 | 0.7477 | 0.7564 | 0.7537 |
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+ | 0.7242 | 5.0 | 345 | 0.6435 | 0.7860 | 0.7841 | 0.7861 | 0.7860 |
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+ | 0.6305 | 6.0 | 414 | 0.5543 | 0.8173 | 0.8156 | 0.8200 | 0.8173 |
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+ | 0.562 | 7.0 | 483 | 0.4860 | 0.8392 | 0.8383 | 0.8411 | 0.8392 |
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+ | 0.5042 | 8.0 | 552 | 0.4474 | 0.8528 | 0.8514 | 0.8546 | 0.8528 |
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+ | 0.4535 | 9.0 | 621 | 0.4213 | 0.8580 | 0.8579 | 0.8590 | 0.8580 |
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+ | 0.4338 | 10.0 | 690 | 0.4106 | 0.8591 | 0.8578 | 0.8605 | 0.8591 |
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+ | 0.4026 | 11.0 | 759 | 0.4064 | 0.8622 | 0.8615 | 0.8632 | 0.8622 |
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+ | 0.3861 | 12.0 | 828 | 0.3874 | 0.8737 | 0.8728 | 0.8733 | 0.8737 |
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+ | 0.3709 | 13.0 | 897 | 0.3841 | 0.8706 | 0.8696 | 0.8701 | 0.8706 |
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+ | 0.3592 | 14.0 | 966 | 0.3841 | 0.8716 | 0.8709 | 0.8714 | 0.8716 |
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+ | 0.3475 | 15.0 | 1035 | 0.3834 | 0.8737 | 0.8728 | 0.8732 | 0.8737 |
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+ | 0.3537 | 16.0 | 1104 | 0.3805 | 0.8727 | 0.8717 | 0.8722 | 0.8727 |
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+ | 0.3317 | 17.0 | 1173 | 0.3775 | 0.8747 | 0.8739 | 0.8741 | 0.8747 |
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+ | 0.323 | 18.0 | 1242 | 0.3759 | 0.8727 | 0.8718 | 0.8721 | 0.8727 |
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+ | 0.3327 | 19.0 | 1311 | 0.3776 | 0.8758 | 0.8750 | 0.8756 | 0.8758 |
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+ | 0.3339 | 20.0 | 1380 | 0.3760 | 0.8758 | 0.8750 | 0.8753 | 0.8758 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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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