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distilbert-finetuned-go-emotions_dataset

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distilbert
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  1. README.md +10 -8
  2. model.safetensors +1 -1
  3. runs/Jun06_07-04-28_8b69e68f16d6/events.out.tfevents.1717657474.8b69e68f16d6.214.0 +2 -2
  4. runs/Jun06_07-04-28_8b69e68f16d6/events.out.tfevents.1717658304.8b69e68f16d6.214.1 +3 -0
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2950
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- - Accuracy: 0.6253
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- - F1: 0.5996
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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: 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=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.8659 | 1.0 | 568 | 1.4169 | 0.6075 | 0.5660 |
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- | 1.3648 | 2.0 | 1136 | 1.3101 | 0.6194 | 0.5863 |
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- | 1.2379 | 3.0 | 1704 | 1.2950 | 0.6253 | 0.5996 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5221
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+ - Accuracy: 0.5844
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+ - F1: 0.5241
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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: 1e-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=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 262 | 1.9841 | 0.4993 | 0.3718 |
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+ | 2.1649 | 2.0 | 524 | 1.6903 | 0.5508 | 0.4546 |
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+ | 2.1649 | 3.0 | 786 | 1.5779 | 0.5732 | 0.4992 |
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+ | 1.5746 | 4.0 | 1048 | 1.5320 | 0.5800 | 0.5114 |
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+ | 1.5746 | 5.0 | 1310 | 1.5221 | 0.5844 | 0.5241 |
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  ### Framework versions
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