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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- go_emotions
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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: roberta-large-go-emotions-2
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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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# roberta-large-go-emotions-2
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This model is a fine-tuned version of [
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- F1: 0.5111
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## Model description
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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: 128
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- eval_batch_size: 128
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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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- num_epochs:
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### Training results
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| Training Loss | Epoch |
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| No log | 1.0 |
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| 0.
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| 0.
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### Framework versions
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- go_emotions
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metrics:
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- f1
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model-index:
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- name: roberta-large-go-emotions-2
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: go_emotions
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type: multilabel_classification
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config: simplified
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split: test
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args: simplified
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metrics:
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- name: F1
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type: f1
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value: 0.5180
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: go_emotions
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type: multilabel_classification
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config: simplified
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split: validation
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args: simplified
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metrics:
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- name: F1
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type: f1
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value: 0.5203
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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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# roberta-large-go-emotions-2
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset. It achieves the following results on the test set (with a threshold of 0.15):
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- Accuracy: 0.44020
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- Precision: 0.5041
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- Recall: 0.5461
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- F1: 0.5180
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## Model description
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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: 128
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- eval_batch_size: 128
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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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- num_epochs: 9
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### Training results
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| Training Loss | Epoch | Validation Loss | Accuracy | Precision | Recall | F1 |
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| ------------- | ----- | --------------- | -------- | --------- | ------ | ------ |
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| No log | 1.0 | 0.0889 | 0.4043 | 0.4807 | 0.4568 | 0.4446 |
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| 0.1062 | 2.0 | 0.0828 | 0.4113 | 0.4608 | 0.5363 | 0.4868 |
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| 0.1062 | 3.0 | 0.0813 | 0.4201 | 0.5198 | 0.5612 | 0.5227 |
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| No log | 4.0 | 0.0862 | 0.4292 | 0.5012 | 0.5558 | 0.5208 |
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| 0.0597 | 5.0 | 0.0924 | 0.4329 | 0.5164 | 0.5362 | 0.5151 |
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| 0.0597 | 6.0 | 0.0956 | 0.4445 | 0.5241 | 0.5328 | 0.5161 |
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| No log | 7.0 | 0.0962 | 0.4648 | 0.5138 | 0.5277 | 0.5151 |
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| 0.0458 | 8.0 | 0.0962 | 0.4462 | 0.5257 | 0.5270 | 0.5203 |
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| 0.0458 | 9.0 | 0.1029 | 0.4432 | 0.5076 | 0.5249 | 0.5111 |
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### Framework versions
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