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emotion_detection_conversations/README.md
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---
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license: apache-2.0
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tags:
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- simplification
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: emotion_detection_conversations
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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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# emotion_detection_conversations
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This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 9.3107
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- Precision: 0.1293
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- Recall: 0.1319
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- F1: 0.0835
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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: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| No log | 1.0 | 151 | 3.8943 | 0.0239 | 0.0789 | 0.0352 |
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| No log | 2.0 | 302 | 4.8539 | 0.0666 | 0.0717 | 0.0585 |
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| No log | 3.0 | 453 | 5.8488 | 0.0534 | 0.1240 | 0.0679 |
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| 1.3425 | 4.0 | 604 | 6.7323 | 0.1186 | 0.1234 | 0.0753 |
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| 1.3425 | 5.0 | 755 | 7.5279 | 0.0712 | 0.1343 | 0.0680 |
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| 1.3425 | 6.0 | 906 | 7.9147 | 0.0858 | 0.1239 | 0.0774 |
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| 0.331 | 7.0 | 1057 | 8.5365 | 0.0961 | 0.1386 | 0.0821 |
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| 0.331 | 8.0 | 1208 | 8.9932 | 0.1065 | 0.1447 | 0.0882 |
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| 0.331 | 9.0 | 1359 | 9.3523 | 0.1292 | 0.1319 | 0.0831 |
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| 0.1291 | 10.0 | 1510 | 9.3107 | 0.1293 | 0.1319 | 0.0835 |
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### Framework versions
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- Transformers 4.27.2
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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